three essays on innovation dynamics: category emergence

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THREE ESSAYS ON INNOVATION DYNAMICS: CATEGORY EMERGENCE,

COMMERCIALIZATION, AND ETHICAL GOVERNANCE OF INNOVATION

A dissertation submitted in partial fulfillment of the requirements for the degree of

PHD IN BUSINESS ADMINISTRATION

FROM

ESSEC BUSINESS SCHOOL

and for the degree of

DOCTEUR EN SCIENCES DE GESTION

DE L’ECOLE DOCTORALE

«ECONOMIE, MANAGEMENT, MATHEMATIQUES, PHYSIQUE ET SCIENCES INFORMATIQUES»

ED 405

UNIVERSITE PARIS-SEINE

Presented and defended publicly on 21 January 2020 by

Subhadeep DATTA

JURY

Stoyan V. SGOUREV Supervisor

Professor, ESSEC Business School (Cergy, France)

Anca METIU Examiner /

Committee

Chair

Professor, ESSEC Business School (Cergy, France)

Philip MEISSNER Referee Professor, ESCP Europe Business School (Berlin, Germany)

Marco BOTTURA Referee

Associate Professor, EDC Paris Business School (Paris,

France)

Kevyn YONG Examiner Chief Learning Officer, Singapore Institute of Management

(Singapore)

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Table of contents

Introduction………………………………………………………………………………...3

Essay one……………………………………………………………………………………8

References – essay one…………………………………………………………….41

Appendix – essay one………………………………………………………………53

Essay two……………………………………………………………………………………59

References – essay two……………………………………………………………..82

Appendix – essay two………………………………………………………………91

Essay three………………………………………………………………………………….93

References – essay three…………………………………………………………..115

Appendix – essay three……………………………………………………………122

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Introduction

Three essays on innovation dynamics: category emergence, commercialization, and

ethical governance of innovation

Subhadeep DATTA

ESSEC Business School

This dissertation contains three essays on the theme of industry-level innovation and

different aspects of innovation. The essays contribute to the literatures of institutional theory,

categories, commercialization, evaluation, responsible innovation, and governance of

innovation. Over the past few decades, the world has observed a wave of commercialization

which has changed the way many actions are performed. One of the key features has been that

of the state relinquishing its control over many activities that are now performed in the market.

This wave of commercialization has given rise to some unique and innovative forms of

organization within existing industries. Some of the outcomes of these innovative forms of

organizations are the emergence of new categories, hybridization of existing categories,

tensions between various stakeholders because of the hybridizations, emergence of new

performance evaluation systems, and new questions being raised on ethical and moral grounds

concerning the application of such innovations. In this dissertation I have attempted to address

some of these aforementioned aspects of industry-level innovation.

Essay one studies the mechanism commercialization of cultural industries in the

context of sports. More specifically, I look into the emergence of a new commercially

motivated cricket league in India called the Indian Premier League (IPL). Deviations from

existing paradigms can produce dramatic outcomes - both positive and negative, and history is

full of such accounts. Vincent van Gogh developed a radically new artistic style but could sell

only one painting during his lifetime. Whereas, another deviant painting in the early 20th

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century, that was initially dismissed by its audience as “cataclysm”, went on to become one of

the most widely recognized artworks of the 20th century that started the cubist movement. The

painting in question was Les Demoiselles d’Avignon and the name of the artist was Pablo

Picasso (for details see Sgourev, 2013). Similarly, the sport of cricket in India went through a

radical transformation with the introduction of the franchisee based, commercially motivated,

and radically designed IPL in 2008. Initially, the league was subject to criticism from various

quarters as “vulgar” and “not cricket”. However, in a matter of just ten years, the IPL has gone

on to become the sixth most watch sports league in the world. Despite the predominance of

commercialization, our understanding of the mechanisms through which commercialization

happens is fairly limited. Furthermore, commercialization of cultural industries has been

completely ignored by extant works in this field. In this study, I propose a two-stage model of

commercialization and posit that commercialization happens through a mechanism of layover

of an exogenous, alien (institutional) logic on an incumbent logic, and that the incoming logic

becomes more dominant in micro-mechanisms of the commercialized category / industry like

performance evaluation. I also validate this econometrically using salary data of cricket players

in the IPL.

Essay two builds up on essay one and sheds light on the mechanisms through which

new categories emerge because of commercialization of industries. Most studies on the process

of categorization focus on the downstream side of categories and their impact on organizational

performance. The formative processes of categories have historically received limited

scholarly attention. Literature suggests that borrowing external categorical codes from other

domains is a mechanism through which new categories are created. But the exact nature of the

borrowing, that is, which codes are borrowed, and if the process is random or strategic, is still

not clearly understood. I address this gap by studying a new commercially motivated soccer

league in India, called the Indian Super League (ISL) that started in 2014 after the tremendous

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commercial success of the IPL. Econometric analysis of data on player evaluation at the ISL

suggests that the ISL borrowed its codes from the IPL, and only those codes were borrowed

that led to the commercial success of IPL. In the IPL, the clubs are owned by Bollywood stars

and industry leaders, who bring in the entertainment (institutional) logic in the domain of

sports, which leads to the sport’s commercialization. In the case of the ISL, the clubs are owned

by Bollywood stars, industry leaders, as well as famous Indian cricketers, who bring in similar

sets of entertainment logics in the ISL, which they borrow from the IPL. Thus, this study

enriches the borrowing mechanism of category formation by elaborating the mechanism in

greater detail.

Essay three also focuses on innovation, albeit a different aspect of innovation – the

ethical aspect. Innovation is a key driver of the economic performance of firms and the

development of national economies. However, many innovation projects raise serious ethical

questions which must be handled to minimize the negative impacts of such innovation. Extant

research has paid limited attention to how such ethical questions are handled by relevant

stakeholders. I address this gap by drawing on the concepts of “responsible innovation” and

“effectuation” with an aim to propose a process model of ethical governance of such projects.

This would help us understand how the principles of sustainability and responsibility are

applied and what practices reduce the potential negative impacts in radical innovation projects.

I focus exclusively on projects in the domain of artificial intelligence.

Throughout the entire duration of my studies that resulted in these three essays, I tried

by best to reinforce my intuitions about the studied phenomena with thorough examinations of

the literature and diligent analysis of objective data to arrive at the conclusions. The hope is to

contribute, even if in a minor, humble way, to the ocean of literature that has enriched

management and organization theory over the past several decades. My introduction to my

dissertation would be incomplete if I fail to mention the amazing guidance and support that I

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have received from my advisor, Prof. Stoyan V. Sgourev. My development as a scholar at

ESSEC was predominantly because of Stoyan’s support both in my professional endeavors and

my personal struggles. He always showed confidence in my abilities as a scholar. I discussed

with him my plans with respect to teaching in various programs once I start my academic

career, and I will be eternally indebted to him for helping me develop those needed skills by

letting me teach several sessions in his courses at the Grande Ecole and the global MBA levels

at ESSEC. He has been a great mentor and an even greater friend, and I sincerely hope that we

will continue to work together in the future on projects that are of interest to both of us.

Equally significant was the nurturing mentorship that I have received from Dr. Kevyn

Yong. Kevyn and I had started discussing about working together on a project when I met him

for the first time in an elective course that he was teaching us. I am extremely happy that we

finally managed to do so, and that work is part of my dissertation. We have big plans regarding

this project and I sincerely hope that eventually we will be able to make it a home run. Also,

during my visit to the Singapore campus of ESSEC, I felt at home predominantly because of

Kevyn’s hospitality as the Dean of the Singapore campus at that time. My sincere gratitude to

him for being an amazing mentor and helping me develop my skills as a teacher by letting me

sit in his executive education classes.

I would also like to thank Dr. Brandon Lee, who hosted me at the Melbourne Business

School during my stay there as a visiting PhD scholar, Dr. Jan Lepoutre for our discussions on

emerging markets which gave me several ideas while writing my dissertation, Dr. Elisa Operti,

Dr. Anca Metiu, Dr. Raymond-Alain Thietart, and Dr. Gilles van Wijk for their outstanding

mentorship at ESSEC.

I would be doing unforgivable injustice if I fail to mention the support that the PhD

office at ESSEC has given me from behind the scene. I am eternally thankful to Mrs. Lina

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Prevost and Mrs. Christine Gil, who were always there to find solutions to every administrative

issue that came up in the past five years.

Last but not the least, I would like to thank my amazing family and friends, as without

them, I would not have ever been able to cross the finish line of the PhD marathon.

With gratitude,

Subhadeep DATTA

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Essay One

Wicket game: The commercialization of cricket in India and its impact on performance

evaluation of professional cricketers

Abstract

Commercialization is a widespread phenomenon and yet, relatively little is known

about the mechanisms of commercialization, particularly that of the cultural industries. I

address that gap in this paper by studying the evolution of cricket in India, leading to its

eventual commercialization. In doing so, I propose a two-stage model of commercialization

and highlight the roles that institutional entrepreneurs play in those respective stages.

Furthermore, I uncover the mechanism of commercialization through econometric analysis of

the salaries of cricket players at the franchisee-based cricket league called the Indian Premier

League. I demonstrate that commercialization predominantly happens by the layover of new

institutional logics over erstwhile logics and that the overlaying logic becomes dominant driver

of evaluation in the changed markets. Subsequently, the paper contributes to the literatures of

commercialization, institutional logics, and evaluation.

Keywords : Commercialization, cultural industries, cricket, institutional logics, evaluation

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Introduction

The past few decades have seen a gradual increase in the phenomenon of

commercialization in various domains and industries. Commercialization has led to the

development of new market structures and organizational forms. In these new forms, the

domains are characterized by the simultaneous existence of multiple, often conflicting

institutional logics (e.g. Kallio et al., 2016). Most studies in this vein, investigate the

commercialization of commodities. Commercialization of cultural industries like sports, arts,

and academia have received only limited scholarly attention (see Lawrence & Phillips, 2002).

Cultural industries are unique as the mechanisms of commercialization of such domains are

different from what is observed in traditional industries. The predominant scholarly focus on

the commercialization of traditional industries has enriched relevant theories in this domain,

but such theories are limited in understanding the various challenges and mechanisms of the

commercialization of cultural industries (Lawrence & Phillips, 2002). Recent literature has

revised and extended the definition of cultural industries to include professional sport in its

purview (Hirsch, 2000, p. 359). Subsequently, this paper fills the identified conceptual gap by

studying the evolution and eventual commercialization of the sport of cricket in India. This

paper fills that conceptual gap by studying the commercialization of cricket in India in the

context of the newly created franchisee based cricket league called the Indian Premier League

(IPL).

The study is motivated by the key research questions: What is commercialization? How

does it happen in cultural industries? Extant research in this vein suggests the “overlaying of

logics” as an expression of commercialization (e.g. Sgourev, 2018; Kallio et al., 2016). But

most studies fall short in explaining the process from a dynamic perspective. I analyze relevant

literature and study the evolution of cricket in India from the pre-independence times, when

cricket used to be governed by the erstwhile codes of the upper-class Victorian elites to the

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present day, when cricket is dominated by commercially motivated logics. Subsequently, I

propose a two-stage model of commercialization of cricket in India, where the erstwhile

cultural artefact of cricket was first converted into a mass commodity through strategic political

rewiring. This mass-product underwent a second phase of rewiring through a symbiotic nexus

with Bollywood, that led to the eventual commercialization of the sport in India.

I find that in new hybrid-like market structures, multiple logics do not get overlaid

magically. The process of overlaying of logics takes time, is orchestrated by institutional

entrepreneurs, and is aided by favorable market conditions. Furthermore, evaluations in these

hybrid, commercial artefacts are dominated by the once-alien, overlaying logic rather than the

underlying, original logic. I validate this econometrically by studying the remuneration of

cricket players at the IPL over the time period 2008-2017. I find that evaluation of the cricketers

is mostly influenced by ascriptive factors like media visibility and demography. Cricketers,

particularly Indian cricketers with the highest media visibility attract the highest remuneration

in this study. In absolute terms, this may be interpreted as bias or discrimination. But this kind

of “apparent bias” makes perfect sense and is logically explainable in the light of

commercialization. I argue that commercialization of cricket in India happens through the

overlaying of the entertainment logics over the athletic logics of the erstwhile sport. These

entertainment logics are brought into the evaluation by the Bollywood stars, who own teams in

the tournament. In Bollywood, and in the film industry in general, visibility is a key

determinant of evaluation and remuneration. I observe the same mechanisms of evaluation in

the data from cricket.

Thus, this paper contributes to the literature of commercialization and institutional

logics by detailing the mechanism of logics overlay though which commercialization happens

in cultural industries, particularly in the domain of sports. Furthermore, unlike most studies in

commercialization, which investigate the effect of commercialization of performance and the

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development of new performance measures and new performance management systems, I look

into the effect of commercialization on evaluation. Thus, the paper also contributes by linking

the two previously disparate literatures of institutional logics and evaluation.

Theoretical background

Mechanisms of commercialization

Over the past several decades, there has been a gradual emergence of commercialization

which has resulted in marked differences in the ways certain market activities are performed.

Activities, which were previously controlled by the state, are now being performed in the

market, which has witnessed the emergence of non-state private players (Keohane & Nye,

2001). In the process, the state lost or relinquished its control over such activities. The impact

of commercialization and open market dynamics also started to be observed in varied cultural

domains like arts (e.g. Sgourev, 2018), academia (e.g. Kallio et al., 2016), and sports (e.g. Celik

& Ince-Yenilmez, 2017). Commercialization of these domains have led to the development of

new hybrid organizational and market structures, where the domains are being orchestrated by

the simultaneous existence of multiple, often conflicting institutional logics. Even cultural

industries have not escaped the wave of commercialization. Cultural products are embedded in

our societal structures and are “consumed in an act of interpretation rather than being used in

some practical way to solve some practical problem” (Lawrence & Phillips, 2002: 431). The

uniqueness of commercialization of cultural industries is that, the management and

commercialization of such products are concerned more about the sustenance of the symbolic

aspects than about production efficiency of those products. In other words, the mechanisms of

commercialization for such products aren’t the same as those observed in the

commercialization of commodities, which follows the standard S-curve of the industry

development life-cycle. In traditional industries, products and commodities are phased out as

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the market demand changes because of commercialization and new products and commodities

are introduced in the markets. But in cultural industries, it is practically impossible to phase

out an erstwhile product or artifact. For example, it is impossible to phase out academia, or a

particular form of art, or a particular sport. How does, then, commercialization happen in such

cultural industries? Who brings about commercialization in such industries and how?

Traditional management research is yet to look into such mechanisms in greater detail and there

is a major void in the knowledge repository in this vein. This skewed scholarly focus on the

commercialization of traditional industries has enriched relevant theories in this domain, but

such theories are limited in understanding the various challenges and mechanisms of the

commercialization of cultural products (Lawrence & Phillips, 2002).

The process of commercialization exerts a powerful influence across a variety of market

domains. One of its most salient influences is observed in the creation of new market structures

and organizational forms and the re-shaping of existing structures and forms (e.g., Garcia-

Parpet, 2007; Huault & Rainelli-Weiss, 2011; Glaser, Fiss, & Kennedy, 2016). Most of the

studies in this vein build on previous work regarding how the expansion of markets happen in

areas that were previously not influenced by market relationships (Zelizer, 1979; Carruthers &

Stinchcombe, 1999; Garcia-Parpet, 2007). Aspers (2013) observes that there are three

prerequisites for the construction of new markets: an agreement about what the market is about

(i.e., what kind of product or service is exchanged), how things are done in the market (i.e., the

culture surrounding market transactions), and how the economic worth of the offer is

determined (e.g., by haggling, bargaining, fixed prices, auctions, etc.) (see also Ahrne, Aspers,

& Brunsson, 2015). Building on these bedrocks of market creation, a number of prior studies

have looked into the ways new market categories emerge (e.g., Rao, Monin, & Durand, 2003;

Kennedy, 2008; Khaire & Wadhwani, 2010) and how shared meanings among audiences

orchestrate market creation (e.g., Koçak, Hannan, & Hsu, 2014; Navis & Glynn, 2010).

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In the specific case of commercialization of cultural industries, or similar industries,

the new post-commercialization market and organizational forms often portray the co-

existence of multiple institutional logics. Extant research has arrived at divergent conclusions

regarding the consequences of logic multiplicity (Besharov & Smith, 2014). Some scholars

associate the existence of multiple logics in organizations with conflict (Battilana & Dorado,

2010; Zilber,2002). However, others have found cases of logic coexistence (McPherson &

Sauder, 2013) and logic blending (Binder, 2007). Furthermore, some scholars argue that the

presence of multiple logics can hinder performance and even lead to organizational failure

(Tracey, Phillips, & Jarvis, 2011). Contrasting cases also lead to the inference that logic

multiplicity could make organizations more sustainable and innovative (Jay, 2012; Kraatz &

Block, 2008). Each institutional logic represents a distinct set of values and principles from

various realms of our socio-cultural existence. However, when logics overlap, actors often

draw on multiple logics both from across and within social domains (Friedland & Alford,

1991). Subsequently, some studies demonstrate the replacement of one logic by another

(Thornton, 2004), while others describe a blending process, which is characterized by the

combination of the different elements of multiple logics into a new one (Stark, 1996). Still

others highlight a process of assimilation in which elements of one logic are subsumed within

those of another (Murray, 2010; Townley, 1997).

Institutional logics

The concept of institutional logics was put forward by Alford & Friedland (1985). They

used the term logics to describe the practices and beliefs that are integral parts of institutions

of modern western societies (Thornton & Ocasio, 2008). The concept was further developed

and was used to explore the interrelationships between organizations, society and individuals

by Friedland & Alford (1991). In their working paper that reviews the literature on institutional

logics, Haveman and Gualtieri define logics as “systems of cultural elements (values, beliefs,

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and normative expectations) by which people, groups, and organizations make sense of and

evaluate their everyday activities and organize those activities in time and space” (Haveman &

Gualtieri, 2017: 2). This definition of logics encompasses organizational and markets structures

and help us understand how organizations and markets function.

Logics shape behavior by setting expectations for social relationships (Goodrick &

Reay, 2011). Research on the influence of logics on behavior shows that behavior, guided by

logics, helps to maintain consistency within a field (Scott, 2008). For example, Goodrick

(2002) demonstrated that a rise in empirical research in management education resulted from

a shift in logics from vocational to scientific. It has also been found that there is an association

between different logics and the types of actors and geographical communities (Goodrick &

Reay, 2011). For example, physicians are guided by the professional logic while health-care

managers are guided by corporate logic (Reay & Hinings, 2009).

In recent times, we observe market structures being changed by various factors and

these changes result in organizational forms that sport two conflicting institutional logics

within the organizational core (e.g., Battilana & Dorado, 2010; Jay, 2012; Pache & Santos,

2013). Social enterprises combine elements of social welfare, development, or sustainability

logics with elements of market or corporate logics (Smith, Gonin, & Besharov, 2013). The

phenomenon of hybridization can also be viewed as the phenomena of category straddling, as

highlighted in the literature on categories. Category straddling essentially refers to an

organization trying to imbibe characteristics from multiple categories, which, for all practical

purposes is the combination of conflicting institutional logics in an organization.

Extant literature has highlighted the negative effects of category straddling or

hybridization, where such organizations are evaluated negatively by their audience (e.g. Alexy

& George, 2013; Hannan, 2010; Hannan, Polos, & Carroll, 2011; Zuckerman, 1999). The

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literature proposes three reasons for this negativity (Durand & Paolella, 2013). First, category

straddling or hybridization impacts identities, which become less focused in the eye of the

audience and hence is less appreciated (Negro, Hannan & Rao, 2010). Second, such behavior

is believed to have a negative impact on organizational capabilities because of their

membership in multiple categories or their incorporation of multiple institutional logics (Hsu,

2006). Finally, straddling impacts the evaluation of organizations by audiences, whose

evaluation capacities are overstrained (Zuckerman, 1999).

Greenwood et al. (2011: 332) conclude that most studies implicitly assume that logics

are “inherently incompatible”. This is illustrated by their own definition of institutional

complexity as situations where organizations are confronted with ‘incompatible prescriptions

from multiple institutional logics’ (Greenwood et al., 2011: 318). However, there are

indications that multiple logics can coexist and maybe even be combined within an

organization or an organizational practice: so-called hybrids (e.g. Battilana & Dorado, 2010;

Dunn & Jones, 2010). A hybrid is an organization that combines different institutional logics

(Battilana & Dorado, 2010).

In recent times, such category straddling and hybridity is often necessitated by the

importation of market logics and the reshaping of markets as a result of entrepreneuring, and

even rewarded rather than penalized. Accordingly, novel market structures and business

models are developed, legitimized, institutionalized and diffused. This is evident in the past

few decades with the rapid commercialization of cultural industries like academia, arts, and

sports.

Commercialization of academia

Free-market policies started being applied in the domain of higher education since the

1990s (Aarrevaara, Dobson, & Elander, 2009). Subsequently, academia is started to be more

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market oriented and marketized (Czarniawska & Genell, 2002). It is now considered normal

for educational service providers to enter into competition with each other (Engwall, 2007) and

to market themselves to prospective customers (Ng & Forbes, 2009). On one hand, they are

expected to meet globally set quality standards, while on the other they need to differentiate

themselves from competition (Kallio et al., 2016). In an attempt to conform with these new set

of logics, educational institutions systematically started to clarify their strategic goals

(Patterson, 2001) and to exercise commensurate marketing and management strategies in order

to create favorable perceptions among stakeholders (Aspara et al., 2014; Chapleo, 2010;

Lowrie, 2007; Waeraas & Solbakk, 2009). They also started to introduce novel academic career

systems to attract top talents from all over the globe (Herbert & Tienari, 2013).

This hybridity of the academic vocation, marked by the coexistence of managerial and

educational institutional logics, has been observed in United Kingdom (Chandler, Barry, &

Clark, 2002), the Netherlands (Sousa, de Nijs, & Hendriks, 2010), the Nordic countries

(Czarniawska & Genell, 2002), Germany (Teichler, 2011) and France (Boitier & Reviere,

2013). Of course, there are local variations in the way and the pace such commercialization of

the academic vocation has happened in different countries (Czarniawska & Genell, 2002).

Nonetheless, research has established that overall transformation has been extremely similar in

the western countries and beyond (Wedlin, 2008). Such commercialization has resulted in the

“commodification” (Willmott, 1995) or “McDonaldization” of higher education (Parker &

Jary, 1995), where universities are run like businesses (Chandler et al., 2002; Parker, 2014).

The nature of the work and performance evaluation of academics in universities are

also starting to change and are getting influenced by the strategic goals that are set for the

respective universities (Patterson, 2001; Sousa et al., 2010). Close connections of academics

with business and industry, in addition to carrying out usual academic responsibilities, is

gaining more and more salience (Henkel, 2005). New performance evaluation systems are

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being introduced that measure performance in terms of value creation. Such systems are

changing the logics of academic work in general and also the individuals who do such work

(Marginson, 2008; ter Bogt & Scapens, 2012; Ylijoki, 2005). The intention is to compare how

the university compares with competitors, whether it manages to acquire relevant

accreditations and where it stands in various university rankings (Wedlin, 2008). Overall, the

educational institutions and academics are now governed by new institutional logics, that root

for competition and short-term results rather than collegiality and academic discussion (Kallio

et al., 2016).

Commercialization of arts

The domain of arts has also been commercialized in similar lines. In the field of arts, it

is often believed that money and arts are orthogonal, and that money belittles the aesthetic

value of arts (Velthuis, 2003). The worlds of arts and market forces were often deemed to be

hostile to one another (Bourdieu, 1996). However, in current times, artworks fetch record prices

at auctions. This corroborates the apparently irreversible invasion of money in the domain of

arts and the burgeoning “commodification” or “financialization” of arts (Boll, 2011; Horowitz,

2014). This ever-increasing domination of art by market forces (e.g., Harouel, 2015) is

manifested by the growing interest of investors and bankers in collecting arts (Sgourev, 2018),

by the explosive rise of prices for art of debatable quality, and the diffusion speculation in the

determination of art prices, a practice, that has its origins in the financial markets (Horowitz,

2014).

The practice of speculation to determine art prices opens up the opportunity to create

new market categories rather than exploiting existing ones (Sgourev, 2018). Literature has

identified a bidirectional relationship between the artistic value and the monetary value of

artworks. The traditional mechanism, where the artistic value is expressed as a function of

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money is termed as monetization. In this mechanism, the artwork in question is deemed as an

investment artefact or is exploited as a source of income (e.g. Horowitz, 2014). The second

mechanism, “Monet-ization”, is a reverse one where experimental, dubious artwork is imbued

with desirable artistic qualities and the corresponding monetary resources are overlaid with

artistic meaning (Sgourev, 2018).

Commercialization of sports

Another salient cultural industry that has been affected by the wave of

commercialization, is sports. Commercialization of sports can be broadly defined as the

invasion and involvement of organizations of commercial interest in the domain of sports,

which is largely governed by independent, non-commercial bodies or boards. Such boards,

although not always governmental, function in many respects as typical bureaucratic state-like

organizations. They subscribe to values which are very different from the values that the

commercial organizations subscribe to. Commercialization takes place through two broad

mechanisms (Yeravdekar, 2013). First, the relationship between an organization and its

members may transform. This is a purely internal mode of commercialization where the nature

of an organizations essentially changes through internal amendments. Second,

commercialization can take place when external commercial organizations collaborate with

non-commercial organizations (e.g. the boards governing sports) to design, create and finance

the production of a collective output. The collective output usually consists of values that are

jointly subscribed to and shared by the two collaborating bodies. Some of the early models of

commercialization like the ones proposed by James (1983) and Schiff & Weisbrod (1991) posit

that commercialization is usually a product driven phenomenon and the associated markets are

usually governed by external forces. While the product is consumer-centric, it is designed by

market participants and satisfies commercial interests.

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Evolution of cricket in India and its subsequent commercialization

Changes in the domain of cultural industries is often led by institutional entrepreneurs

or interpretive activists (Qureshi, Kistruck, & Bhatt, 2016) who have the “symbolic power”

(Bourdieu, 1991) to impose their own interpretations of the cultural object on others.

Stamatov’s account of how interpretive activists used symbolism and formal codes of Verdi’s

operas to politicize a cultural artifact is a salient example (Stamatov, 2002). Institutional

entrepreneurs are defined as “change agents who, whether or not they initially intended to

change their institutional environment, initiate, and actively participate in the implementation

of changes that diverge from existing institutions” (Battilana, Leca, & Boxenbaum, 2009, p.

70). In the following sections, I will uncover the roles played by two such institutional

entrepreneurs or interpretive activists, who changed the status-quo of cricket and let to the

commercialization of the sport in India.

The context of this study is the game of cricket, a franchisee-based cricket league in

India in particular, called the Indian Premier League (IPL). Cricket is a team sport, which

originated in 16th century England and diffused throughout the British Empire in the 19th

century. Cricket has historically been played in several formats. The “test” matches last upto

five days. To do away with the boredom of a five-day game, the more exciting “one-day”

matches were introduced in the late 20th century. The first documented international one day

game was played between Australia and England in the January of 1971. An even shorter

version of the game, called the “Twenty20” or “T20” was introduced in 2003. The first T20

matches were played among the different county teams in England. However, because of the

popularity, this version of the game soon spread to other parts of the world and the first

international T20 match was played between Australia and New Zealand in 2005. A T20 match

is very similar to the one-day match but is a much-shortened version. Traditionally billed as

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an upper-class sport, it has gained immense popularity in India. The evolution of the sport in

India since the colonial times has been rather dramatic.

Phase 1 – indigenization of a foreign cultural artefact into a local mass-sport

Cricket used to be a symbol of Victorian elitism of the English upper class and was

often used to communicate those upper-class values to the English gentlemen (Appadurai,

1995, 2015). In most times of the colonial history, cricket had remained as a segregates sport

in India. The access to the sport and the facilities where the sports could be played was limited

to the British elites and the high-ranking British officers and soldiers stationed in India. The

only Indians who had access to the sport were the crème-de-la-crème of the Indian society –

the princes and the high-ranking government officials (Cashman, 1980; Appadurai, 2015).

During the cricket matches, the English and the Indians played on opposite teams, if they

played together at all. It has been established in literature that in the time period between 1870

and 1930, which is often termed as the high period of the British Raj in colonial India, cricket

was used as an instrument by the Indian princes to ingratiate themselves to the British

authorities, who, in turn, saw cricket as a means for disciplining the Orientals (Appadurai,

2015).

Cricket in this form could never have been commercialized. Had cricket in India

remained within the purview of the elite upper class, the size of that market would not have

been attractive for exploitation by market forces. In this vein, a relatable analogy with English

cricket can be drawn here. In England, cricket continued to retain its aura as an artefact of the

upper-class elites. For sure, the definition of elitism has evolved over time and English cricket

is accessible by the non-upper classes too. However, cricket in England never had the mass

appeal as football (soccer) did. A salient question here is, what happened in India that paved

the road to commercialization of Indian cricket? The answer lies in the underlying sentiments

21

of the freedom movement in India, the subsequent urbanization, the role of media, and the

patronage by corporate houses.

The first stage of cricket becoming a mass sport in India started even before the

nationalist freedom movement led by Gandhi and other prominent Indian leaders became

mainstream. Many Indian princes would have their own teams and those princes would often

recruit coaches from England and Australia, who in turn, would train Indians to acquire

cricketing skills. That was the only way through which small-town Indian boys could enter into

the elite domain of cricket (see Appadurai, 2015). Thus, a cadre of non-elite cricketers were

produced in India who were Indians and who felt that they were genuine cricketers. I argue that

the diffusion of cricket into the working-class Indian segments started happening from that

stage onwards.

Literature suggest that towards the end of the 19th century and the beginning of the 20th

century, the development and diffusion of cricket in India happened under the patronage of

independent promoters. The Indian National Congress (INC) party, which was committed to

the idea of a free nation state was large aloof from the sport and its development (see Appadurai

2015). Cricket started gaining more and more traction in India towards the first three decades

of the 20th century. This time period coincided with the phase when the nationalist movement

against the British under the INC and led by Gandhi was also gaining momentum. Cricket

emerged as a means for the INC to unite the fragmented nation and achieve a bigger end of

gaining independence from the British Raj, by influencing the ordinary lives of young Indians.

There are documents which state how Indian young boys were prevented from playing on a

cricket field in the city of Nagpur during the 1930s, and how local influential politicians, who

were also ardent followers of Gandhi, intervened with a senior British official in Nagpur and

got the boys the right to use the field for playing cricket when it was not in official use (see

Salve, 1987). Such political interventions utilized the undercurrent of public outrage for being

22

kept away from public spaces and turned cricket into a “spice” that would add nationalist flavor

to their resentment. Thus, the nationalist movement did the groundwork for creating a

magnanimous market, which would be exploited by market forces in the future and lead to the

commercialization of cricket in India. The period after India gained independence from the

British Raj saw a trend of rapid urbanization. The government adopted mixed economic

policies and more and more jobs started getting created in the cities which instigated more

people to move to urban areas from the villages. With the Indians getting used to a new kind

of lifestyle, the media and the patronage of corporate houses also contributed substantially to

the diffusion and indigenization of cricket in the subsequent years.

Cricket commentaries that were aired by the All-India Radio (AIR) in the 1930s were

exclusively in English. However, starting in the 1960s, the AIR broadcasted cricket

commentaries in the local languages of Hindi, Tamil, and Bengali in addition to English

(Cashman, 1980). I argue that multilingual radio commentary orchestrated the adoption of

cricket even in the remotest corners of India and helped gain an audience among the masses.

Radios were widely available in India and attracted large audiences at train stations and other

public places. Commentaries on radio in local language helped Indians, even in remote villages,

to understand and absorb the English terminologies of the sport (see Appadurai, 2015). The

reach and interest increased much more with the introduction of television and with cricket

matches getting telecasted into the drawing rooms of the Indians.

Corporate houses in India would recruit young, talented players and keep them in their

rolls. These players would play for those corporate teams in various domestic tournaments.

This practice benefitted the corporates, the players and the nation as a whole in three main

ways. First, the infrastructural support of the corporate houses ensured that the players got

enough freedom to maintain their practice schedules to stay in form. Furthermore, the players

were assured of regular income as employees even after their cricketing careers were over.

23

Second, the corporate houses with the better players performed extremely well in the domestic

tournaments, which increased their visibility among the talent pool. Finally, the

aforementioned visibility succeeded in drawing talented players from semi-urban and rural

regions, thereby adding substantially to the development of social capital in those regions. On

the other hand, the state was able to reap profits from generating national sentiments about the

sport from relatively meager investments on accounts of infrastructure development and social

capital (see Appadurai, 2015). Thus, cricket, which once used to be the cultural relic of the

upper-class British elites, got transformed into a sport for the masses in India. Once the

government decided to migrate to a free market model in 1990, it was only a matter of time

before market forces exploited this huge, “fertilized” market to reap financial benefits. It was

only then, that cricket got truly commercialized in India, and the corporate houses and

Bollywood (the Mumbai based Hindi film industry) played major roles in that story.

Phase 2 – exploitation of a ready market through commercialization by a cricket-Bollywood

nexus

Cricket in India is controlled by the Board of Control for Cricket in India (BCCI). The

governing bodies of cricket in the cricket playing nations have experimented with new forms

of the game in the last four decades to make the game more interesting for the audience and to

make it more media-friendly. In India, this experiment culminated with the design of Indian

Premier League (IPL) in 2008 by Lalit Modi, one of the most influential figures in the

management of the BCCI. Modi, a businessman himself, saw the tremendous financial

opportunity that could be created by exploiting the cricket savvy market in India. Prior to the

design of the IPL, Modi had resulted a seven-fold increase in the revenues of BCCI through

various initiatives between 2005 and 2008 (Wade, 2008). Although BCCI is an independent

body in terms of its affiliation with the state, it used to resemble the state in the way it

functioned until 2008. However, with the conceptualization of the IPL, the rigid boundaries

24

between the state-like controlling board and the market blurred. As the plans of the IPL were

being conceptualized, neither the Government of India nor any of its ministries raised any

objection (Gupta, 2010). Under the stewardship of Modi, cricket ceased to be treated just as a

sport; it got repackaged as a commercial product, heavily influenced by the industries that were

associated with the league. As noted by Moran (2003, p. 88), this phenomenon represented “the

increasing colonization of sport by the market”. This “colonization” involved much more than

just selling the activity. It transformed the way cricket was organized and even played and the

formerly regulated, board controlled eco-system gave way to deregulated market dynamism.

Despite initial doubts expressed by the media and the cricket audience in India, the IPL

became immensely popular immediately after its commencement in 2008. This is largely due

to the shorter duration of the matches, the more aggressive playing styles, and the introduction

of entertainment features like cheerleaders and music-playing DJs into the game. In a country

like India, where cricket and Bollywood are two of the biggest sources of entertainment, there

was a huge market of some kind of fusion between the two. The IPL did just that by introducing

Bollywood to cricket. The development of the IPL saw heavy involvements and investments

from Bollywood. Currently, three of the eight IPL franchises (Kolkata Knight Riders, Kings

IX Punjab, and Rajasthan Royal) are owned by Bollywood stars. Because of IPL’s reach and

popularity, Bollywood stars promote their forthcoming films and songs during the IPL

matches. Even the teams that are not owned by Bollywood stars attempt to cash-in on the

Bollywood appeal by appointing popular Bollywood actors and actresses as their brand

ambassadors. Salient examples of such ambassadorship are Katrina Kaif and Deepika

Padukune (for the “Royal Challengers Bangalore” team), Kareena Kapoor, Anil Kapoor, and

Hrithik Roshan (for the “Mumbai Indians” team) and Akshay Kumar (for the “Delhi

Daredevils” team, which has now been renamed to “Delhi Capitals”) (see Rasul & Proffitt,

2011). This symbiotic nexus between cricket and films is rather obvious because of the

25

potential for rapid growth, popular appeal, and omnipresence for both these previously

orthogonal cultural industries (Bélanger, 2009). However, this commercially lucrative

association would probably not have been possible without the vision and action of Modi.

Traditionally, the movie industry lacked the capability to bring sports directly into the viewers’

homes (Goldlust, 1988). Corporations like Disney, News Corp, and Viacom used to address

this gap by inserting clips from sporting events into their products to attract audiences

(Andrews, 2009). In India, Modi’s IPL emerged as the perfect solution to this problem.

Scholars have studied the potential of sports to be turned into a spectacle through

corporatization and commercialization (e.g., Belanger, 2009; Lowes, 2004; Wenner, 2003). In

India, the amalgamation of Bollywood with cricket has turned the IPL into such an

entertainment spectacle through commodification. The IPL was strategically designed as a

media-friendly enterprise, one that is often compared with the US Super Bowl in terms of

audiences reach and generated advertising revenues (Rasul & Proffitt, 2011). The number of

audiences watching IPL matches on television makes the tournament a holy grail for marketers

who use it to strike a chord with the nation (Dubey, 2011). Television is the only option to

watch IPL matches for those who cannot afford to attend the matches in person or live in cities

where the IPL matches are played. Marketers vie for advertisement spots on television to tap

in that huge middle-class with money to spend. Modi struck a broadcasting deal with Sony that

was reportedly worth £555 million (Hoult, 2008; Majumdar, 2011). Reports indicate that the

major source of revenue for the IPL teams are various forms of sponsorship deals (Pyne, 2016).

On an average, 60% of the revenue come from the sales of media rights to broadcasters around

the world. In addition to that, approximately 20% of the revenues come from brand

sponsorships. The IPL teams tie-up with different brands to display their logos on their shirts,

playing kits and in the home stadiums of the teams. The players also feature in the

advertisements of the main sponsors of the teams. The ticket sales per home game and the prize

26

money from the tournament respectively account for 10% and 5% of the revenue for the teams

(Pyne, 2016). The IPL also created the opportunity for players to earn extraordinary amounts

of money, the likes of which were never witnessed before in the history of cricket (Rasul &

Proffitt, 2011). At the IPL, teams select players in an English auction that happens over a span

of two days. The auctions witness certain players being purchased by teams in exchange of

extraordinary amounts of money.

Thus, from the conceptual analysis of the evolution of cricket in India, I propose a two-

stage model for commercialization of the sport (Figure 1).

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INSERT FIGURE 1 ABOUT HERE

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I argue that cricket as a cultural artefact was unlikely to be commercialized because of

protectionism from the elites in order to preserve the Victorian values that cricket embodied. It

has been observed that in England, cricket has also evolved since the 1930s but not as a

commercial product. Football (soccer), however, was commercialized because of the size of

the market that it appeals to (the blue-collar working class). I observe a similar pattern in India

with cricket. It can be argued that cricket in India would probably not have been

commercialized had it not been turned into a mass product, initially through political

intervention and subsequently by media and corporate patronage. After India adopted a free-

market model, market forces only exploited the ready and fertilized market by repackaging

cricket as a commercial media-friendly product. Subsequently, I posit that in cultural industries

like sports, artefacts indeed need to be “commodified” in some ways to appeal to the masses

before they can be commercialized. Literature establishes that commercialization of cultural

industries happens through overlaying of logics (e.g. Sgourev, 2018; Kallio et al., 2016). I agree

with that view but also argue that this view is limited and a clearer picture of how the multiple

27

logics are overlaid can be obtained from a dynamic perspective of commercialization. I also

validate the dynamism of commercialization though econometric analysis of remunerations of

cricket players at the IPL.

Hypotheses development

The penetration of market logics in the domain of sports influenced the way by which

players are remunerated. Prior to the emergence of the IPL, the BCCI practiced a grade-based

pay system for the cricket players in India. Players were assigned to grades according to their

seniority and performance and all players in a particular grade received the same remuneration.

This practice changed when market logics started to determine player salaries at the IPL. The

new conceptualization of cricket as a component of a commercial value chain raises the

question, whether the fans of the teams should be treated as supporters or consumers. The view

of fans as supporters subscribes to a community oriented political perspective whereas the view

of fans as consumers subscribes to a market perspective. In the context of other sports like

football (soccer), it has been observed that exit is a difficult psychological choice for a fan

(Horton, 1997). However, the way the IPL is designed, it will not be entirely correct to treat

the consumers as dedicated supporters who would not switch sides. The consumers of IPL are

often fickle and are more prone to switching sides in favor of a more attractive team. This is

evident from studying the fan-base of the different teams at the IPL. Not everyone from a city

support their home team. They could also switch to other sports or forms of entertainment,

which would have a direct impact on the commercial aspects of the league. Furthermore, there

is a spillover effect of the status and the fan-following of the Bollywood stars that are connected

with the respective teams, either through ownership or though commercial association. This

spillover effect may also influence fans to switch sides at will. Hence it is expected, that the

player remunerations would be determined in a way, which would incorporate consumer

28

preferences regarding the players in order to incentivize the consumers to stay loyal to the

league and also to the teams.

Having star players with very high media visibility in the team is expected to have a

positive impact on a team’s economic performance. Several researchers have studied the effect

of star on revenues and their findings have been mixed. Some studies have not been able to

establish any relationship between revenues and star involvement (Austin 1989; Ravid 1999).

However, some other studies in the context of films have found evidence that a movie's

revenues increase with the rank of the star associated with it (Ainslie, Drèze, & Zufryden, 2005;

Basuroy, Chatterjee, & Ravid 2003). Furthermore, as brands, star players share comparable

properties with other brands associated with services, physical goods, and movie stars (Keller,

2003). Extant research has established that the benefits assigned to high-status individuals are

a result of not only the individuals’ own status and visibility, but also of the status and visibility

of the individual’s exchange partners. The exchange partners can be other individuals or their

organizations and teams. Thus, teams and individuals can benefit from status spillover effects

just by being associated with partners with higher visibility (Benjamin & Podolny, 1999;

Pollock & Gulati, 2007).

I argue that during the auctions, teams would want to have players with higher visibility,

within the constraints of the total money that they can spend on players during the auctions.

This kind of deliberation and preference for high visibility players would results in them

receiving significantly higher remuneration than others. Thus, I hypothesize:

H1: At the IPL, players with highest media visibility would receive the highest

remunerations, ceteris paribus

Previous research has established that certain groups of workers are preferred by

organizations, earning higher remuneration (e.g. Becker, 1971). Research has examined race

29

and gender as factors of remuneration, with organizations favoring a particular race or gender

over others. Becker (1971) posited that race (demography) based labor market biases could be

propelled by employer prejudice, co-worker discrimination and customer preferences. Some

scholars have argued that market forces will not be able to eliminate biases based on customer

prejudice since teams are expected to have commercial success for signing those players that

the fans want to see (e.g. Kahn, 1991). Therefore, the customer preferences are expected to be

translated into preferences of the market participants (the teams) and hence the same kind of

biases as indicated in customer preferences are portrayed in the behavior of market participants.

For example, a study by Burdekin, Hossfeld, & Smith (2005) that examined consumer

discrimination among National Basketball Association (NBA) fans showed that the racial

composition of teams and their markets are positively correlated. In subsequent research,

Hoang & Rascher (1999) found that match attendance can be increased by matching a team’s

racial composition with that of the population of the team’s market area. However, similar

work by McCormick & Tollison (2001) did not find any such relationship by using data from

the 1980s. A more recent study of soccer players in Major League Soccer also find a mean

effect of birthplace on player salaries (see Celik & Ince-Yenilmez, 2017).

The IPL is said to have resulted in the “commodification” of its stars (Appadurai, 2015).

The best-known Indian cricket stars are now considered as “metacommodities”, who are up for

sale themselves. They also fuel the sale of other commodities through association. Since the

league is based in India and the Indian star players have excessive crowd-pulling capability, in

addition to their commercial impact on the league and the teams, I expect that the highest

remunerations will be offered to the Indian star players. Thus, I hypothesize:

H2: At the IPL, Indian players with highest media visibility would receive the highest

remunerations, ceteris paribus

30

Data and method

I have compiled data for various parameters from multiple sources, and the final

unbalanced panel dataset covers the history of the IPL between 2008 and 2017, features 258

players and 1182 observations. The players come from most of the cricket playing nations of

the world. Indian players represent majority of the players’ pool with 62.02% of the total share.

The Australians (12.79%) represent are the next highest player segment followed by the South

Africans (7.75%). Overall, ten different nationalities are represented in the dataset. Detailed

information about the players’ nationalities are presented in Table 1.

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INSERT TABLE 1 ABOUT HERE

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I collected the performance data of the players from the official IPL website

(www.iplt20.com). Performance in cricket is measured in several dimensions. One of these

dimensions is the specific skill of a player. In terms of skills, a player can belong to one of the

three categories: batsman / wicketkeeper-batsman, bowler and all-rounder. A batsman is a

specialist player who performs the role of batting in the game. These players go in to bat earlier

than the others during the game and their objective is to score as many runs as possible. The

cumulative runs scored by the players represents the total runs of the team in that match. Some

of these batsmen also perform the role of a wicket keeper. An indicator of exceptional

performance is the number of “six” that a batsman hits in a match. The other specialist players

are the bowlers. Their job is to pitch the ball and their objective is to concede as less runs as

possible and get as many players of the opponent team out of the game as possible. This act of

getting opponent players out of the game is called “taking wickets”. When these players get

five players of the opponent team out of the game (technically termed as taking five wickets)

that is considered as an exceptional bowling performance. The third type of players are the all-

31

rounders who can both bat and bowl. Another indicator of a player’s performance, irrespective

of his skills as a batsman or a bowler is the number of “catches” that the player takes during a

match. More details about how the game is played and the various roles of players are available

on the Rules of Sports website . The official IPL website contains detailed performance data

for all the players, which I have compiled and cleaned to develop the database for this study.

I collected the auction data, detailing the players, their base prices and final prices from

several secondary sources of the print and digital media since there is no one single source

where auction data for all the years are available. In addition to the official IPL website, I have

also referred to other specialist sports websites like ESPN Cricinfo (www.espncricinfo.com)

and the online sports section of several newspapers to collect auction prices. The currency for

most of the available auction data was Indian Rupees (INR). However, some websites maintain

data in US Dollars (USD). I have used the average exchange rates between USD and INR for

the respective years to convert the USD data into INR. Data on the prices for some players for

a few years were missing and after consulting the best practices to account for missing data, I

have used multiple imputation method to account for those missing data in the database.

Finally, I collected data regarding the players’ visibility on the media from the Factiva database

of Dow Jones.

Independent and control variables

Age: Age is an indicator of a player’s experience. In the market, experienced resources

are valued and hence is used as a control in the models.

Runs scored (lagged): The total runs scored by players during a match is an indicator

of how well they performed. Other forms of this variable, like average runs scored per match

and strike rate (runs scored per 100 balls) can also influence evaluation. I use the total runs

scored by a player, lagged by a year, as a performance variable.

32

Wickets taken (lagged): Performance for the bowling function of the game can be

measured by various bowling metrics, like number of wickets taken per match and economy

rate (number of runs conceded per six balls bowled). I use the number of wickets taken by a

player, lagged by one year, as another performance variable in the models.

Catches (lagged): I use the number of catches, lagged by a year, as a proxy for fielding

performance.

Specialist (dummy): I also include a variable to control for the role of a player in the

models. This is a dummy variable. In terms of roles, a player can belong to one of the three

categories: batsman / wicketkeeper-batsman, bowler and all-rounder. The first two categories

of players are considered as specialists and I assign them a value of “1”. Players belonging to

the third category are classified as generalists and I assign them a value “0”.

Sixes (lagged): A variable capturing the number of sixes that a player has hit is also

included in the models. This variable is a general indicator of aggressive batting style for the

batsmen.

Five Wickets (lagged): I also include a variable that captures the number of times a

bowler has taken five or more wickets. This is usually considered to be an indicator of

exceptional bowling performance.

Indian (dummy): To capture the role of demography in the models, I created a dummy

variable and assigned the value “1” if a player is Indian. Other players are assigned the value

“0”.

Entertainment (dummy): At the IPL, the owners of the teams belong to contrasting

logics of films, entertainment and other industries. Currently, three of the eight IPL franchises

(Kolkata Knight Riders, Kings IX Punjab, and Rajasthan Royal) are owned by Bollywood stars.

To understand if the respective logics of ownership have any influence on the evaluation of

33

players, I include a dummy variable in the models. I code this variable as “1” if the player plays

for a team that is owned by a Bollywood star. Else, I code it as “0”.

Visibility (lagged): Stardom of players is expressed by the fan-following and the

interest taken in such players by the fans, the media and the markets. To capture media visibility

of players, I have considered a variable in the models that indicates the number of times a

player was mentioned in the media. Data were obtained from the Factiva database of Dow

Jones. As the distribution of the variable was highly skewed, I have taken the natural logarithm

of the number of media-mentions of the players as the explanatory variable for visibility in the

models.

The dependent variables are the base and the final price of a player after the auction

respectively. However, the distributions of these variables are highly skewed. Hence, the

variables included in the models are the square-root versions of the two prices. The regression

estimates are obtained through random effects panel regression analysis using STATA. For this

study, the square-root of the final price is the more salient variable as it captures the evaluation

of players by the market. The choice of random effects model was confirmed by conducting

Hausman test (prob > chi2 = 0.759). Any unobserved heterogeneity with respect to time is

captured in all the models by including a yearly fixed-effect variable.

Results and discussion

The bivariate correlations of all variables used in the analyses are presented in Table 2.

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INSERT TABLE 2 ABOUT HERE

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Findings of the panel regression analyses are presented in Table 3 and Table 4. Table 3

reports the results of analyses with the square-root of the final auction prices of the players,

34

that is, their salaries as the dependent variable. Similarly, Table 4 presents the analyses with

the square-root of the players’ base prices as the dependent variable. These prices are assigned

to the players by the BCCI before the players go into the auction. The number of players (Id)

and the number of observations are also reported in Tables 3 and 4.

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INSERT TABLES 3 AND 4 ABOUT HERE

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The models represented in both the tables are very similar. Model 1 is treated as a

simple baseline, consisting of variables representing experience, objective performance, player

role, player demography and whether players belong to teams owned by Bollywood stars.

These predictor variables are included in all tested models. Model 2 includes a variable

representing players’ visibility. I suspect that the relationship between remuneration and player

visibility is not linear but quadratic as the IPL is packaged as an entertainment product, and the

superstar players with most visibility are expected to attract the highest remunerations. I test

that in Model 3 by adding an additional variable, which is the squared visibility variable from

Model 2. Finally, to test the moderating effect of demography on the relationship between

visibility and remuneration, I include an interaction term in Model 4.

For the analysis, the dependent variable of interest is the players’ final market price

(auction price), which is an expression of the evaluation of the players by the market. However,

it is also interesting to compare the results with the base price as dependent variable to

understand the mechanisms of commercialization and its effects on evaluation for both cases.

Athletics logic and evaluation in the erstwhile form of cricket

Interestingly, I observe that in the base model (Model 1) for both sets of dependent

variables, the key indicators of players’ objective performances are significant predictors of

35

remuneration. In cricket, the performance of a player is measured by the number of runs scored,

which is a proxy for batting performance, the number of wickets taken, which is a proxy for

bowling performance, and the number of catches, which can be argued to be a proxy for fielding

performance. I observe that the coefficients of all three variables are positive and significant.

Thus, I argue that the athletics logic which governed erstwhile cricket, where superior

performance was the driver for higher remuneration is observed in this analysis.

Commercialization of cricket by the layover of entertainment logic

To provide evidence in favor of the argument that commercialization is caused by the

layover of logics, entertainment logic in the case of IPL, I introduce the variable that measures

a player’s visibility in the media in the next model (Model 2). For both sets of dependent

variables, I observe that coefficient of this visibility term is positive and significant (β = 393.54,

p = 0.000 when square-root of the base price is the dependent variable, and β = 411.78, p =

0.000 when square-root of a player’s salary is the dependent variable). I also observe that for

both sets of dependent variables, the influence of objective performance on remuneration is

reduced. For the players’ final salaries, the coefficient of only the number of runs scored is

positive and significant (β = 4.545, p = 0.000). I argue that the higher the number of runs scored

in a match, the greater is the entertainment factor for the audience of the IPL. Thus, both these

outcomes (the positive and significant coefficients of the visibility variable and the runs scored)

lend support to the argument that commercialization is caused by the layover of entertainment

logic over athletics logic and this entertainment logic is dominating player evaluation in IPL.

Furthermore, the results also provide support for Hypothesis 1, that after controlling for

objective performance, the players with higher media-visibility attract higher remuneration.

I also posit that this kind of evaluation mechanism is noticeable in the entertainment

industries like films, where the superstars are highly paid irrespective of the box-office

36

performance of the films or the critical evaluation of the stars. The repackaging of cricket as a

commercial artefact, and the design of IPL as an entertainment product necessitates this kind

of evaluation. Usually, in films, it is the biggest superstars who earn the highest remuneration.

I argue that a similar relationship exists in the IPL, that is, the relationship between visibility

and remuneration is not linear, but quadratic. To test this, I introduce the squared form of the

visibility variable in the analysis (Model 3). When the analysis is done with the players’ salaries

are the dependent variable, the coefficient of this squared visibility variable is positive and

significant (β = 105.760, p =0.000), thereby confirming the non-linear relationship between

visibility and remuneration. Similar results are obtained when the analysis is done with the base

price as the dependent variable (β = 112.900, p = 0.000).

The contextual element of commercialization

As discussed before, demography has sometimes been found to play a substantial role

in determining team composition and a player’s remuneration. Extant research has found mixed

results of the effect of demographic variables on performance and audience participation. I

uncover the contextual role that ascriptive, contingent factors like demography play in

mechanism of commercialization through the lay-over of logics. To do so, I introduce an

interaction term in the model (Model 4). I generate this interaction term by multiplying the

Indian dummy variable with the squared form of the visibility variable. Media reports indicate

that the IPL is one of the most watched sporting leagues in the world. However, the league is

based in India and it is imperative to understand if that factor plays any role in the mechanism

of commercialization of cricket. The findings are rather interesting. When I run the analysis

with the square-root of the base price of the players as the dependent variable (Table 4, Model

4), the coefficient of the interaction term is positive and significant (β = 22.363, p =0.005).

However, when I run the same analysis with the final auction price or the players’ salaries as

the dependent variable, the coefficient of the same term is positive but not significant (Table

37

3, Model 4). These results uncover a very interesting finding about social and historical

embeddedness of the mechanisms of commercialization. The base prices are set by the BCCI,

which is very much ingrained within the socio-political and historical context of the sport in

India. Hence, it is expected that if BCCI were to orchestrate commercialization of cricket in

India through the importation and layover of entertainment logics on cricket, they would assign

the highest evaluation and remuneration to the Indian superstars. However, it is observed that

for the franchisees that bid for players in the auctions, the demographic factor does not seem

to matter much. I argue that for the franchisees, the entertainment factor and the subsequent

commercial outcomes are more important, and it does not matter if a foreign superstar or an

Indian superstar is instrumental in achieving that end. The findings make sense from the point

of view of the consumers and audience too. Indeed, the Indian audience loves the Indian

superstars like MS Dhoni and Virat Kohli. But foreign superstars like Chris Gayle, AB de

Villiers, and David Warner are also equally popular in India and the attendance in the IPL

matches where these players play support this argument. I argue that the IPL audience is more

concerned about the entertainment that they derive from the tournament, and for them, it does

not matter whether an Indian superstar or a foreign superstar provides that entertainment.

Furthermore, IPL matches are telecast not only in India but in other parts of the world as well,

and the evaluation of the players by the market forces reflect corresponding audience demand

in showing no preference for the Indian superstars.

However, I also argue that the effects of commercialization on evaluation are

evolutionary in nature and that there is a temporal dimension attached to it. In other words,

when commercialization happens, it takes some time before the actual nature and impact of

commercialization can be observed on evaluation. This is because the central artefact that

emerges because of commercialization (the IPL in this case) is new and that the uncertainties

related to evaluation of this new artefact resolve over time. I demonstrated in the conceptual

38

analysis of this paper, that there is a temporal dimension to commercialization (expressed

through the two-stage model). On similar lines, I argue that it is true that commercialization

happens through logics layover, but that layover does not happen overnight but happens over

time, and the effects of the layover of these institutional logics can be observed only after a

certain amount of time.

To test this, I split the database into two approximately equal halves and carry out the

analysis as described above. However, I only consider the full model (Model 4) for this analysis

and use the square-root of both the base prices and the final prices of the players as the

dependent variable respectively. The first half consists of 650 observations covering the

timespan 2008-2014, and the second half consists of 532 observations for the timespan 2015-

2017. The results are presented in Table 5.

--------------------------------------------

INSERT TABLE 5 ABOUT HERE

---------------------------------------------

The results reveal that the contextual effect of demography is not observed in the dataset

covering the initial years of the IPL. The coefficients of the interaction variable are not

significant for both sets of dependent variables during the initial years. However, for the dataset

covering the later years of the IPL, the same coefficients are positive and significant (β =

42.902, p = 0.000 when the square root of the base price is the dependent variable, and β =

23.975, p = 0.065 when the square root of the final price is the dependent variable). I argue

that these results uncover the evolutionary nature of the impact of commercialization on

evaluation. It may be admitted that the reduction of the number of observations because of the

splitting of database might have resulted in a certain degree of loss of statistical power.

However, the results are robust and consistent, and it is highly likely that further analysis with

39

more slices of data added to the panel database will result in stronger statistical effects. It would

be interesting to understand what commercial factors lead to the Indian superstar cricketers

attracting the highest remunerations at the IPL in recent years. In the absence of objective data,

it may be speculated that the role that Indian superstar cricketers play in the revenue generation

for the league and for the franchisees through television commercials and other means, has

contributed to this kind of evaluation mechanisms. This could be a viable research project for

the future. Within the scope and the limitations of the current study, I obtain partial support for

Hypothesis 2.

Conclusion

This paper contributes to the literatures of commercialization, evaluation, institutional

logics, and institutional entrepreneurship in several ways.

First, commercialization is a widespread phenomenon of recent times and it leads to

new ways of organizing in markets by changing market structures. The market logics also lead

to the development of various hybrid forms of organization and governance. Even so, very little

is known about the mechanisms of commercialization from a dynamic perspective.

Furthermore, most of extant research in commercialization look into the commercialization of

commodities. Cultural industries, which are also facing the wind of change with respect to

commercialization have received very limited scholarly attention until now. It is imperative to

look into the commercialization mechanisms of cultural, or other closely associated industries.

That way, the existing theories of commercialization could be expanded. This paper addresses

that gap by detailing the mechanism of logics overlay though which commercialization

happens in the domain of sports, a cultural industry. I propose a two-stage model of

commercialization and demonstrate that commercialization happens through the process of

overlaying of new institutional logics over erstwhile institutional logics and that this new

40

“incoming” logic has significant effects in processes like evaluation, after controlling for

objective performance. Furthermore, I highlight the temporal dimension of commercialization

– I demonstrate that commercialization is a two-stage process which takes place over time,

under favorable market conditions and institutional support, and orchestrated by institutional

entrepreneurs or interpretive activists. Furthermore, I also provide evidence that even after the

commercialization of a cultural industry, it takes time for the effects of commercialization to

be manifested on processes like evaluation. In doing so, I contribute to the literatures on

commercialization and institutional logics by establishing a link between the two previously

disparate streams of literatures.

Second, much of the analysis in this paper supports Sarasvathy’s conceptualization of

entrepreneurship as a science of the artificial (Sarasvathy, 2003). One of the key postulates of

Simon’s Science of the Artificial (Simon, 1969) is that within the constraints of natural laws,

our imaginations drive our designs. In other words, entrepreneuring is essentially a function of

what we “can do” rather than what we “should do”. In my analysis, I uncover that both Gandhi

and Modi were driven by an overall vision of that they wanted to achieve through their actions

involving cricket, rather than meticulous planning. Their actions were guided by what could be

made possible in the existing contexts, given the constraints and resources that they had at their

disposal, with an objective of “analogizing” (Johannisson, 2011, p. 140). This finding also

supports the practice theory approach to entrepreneuring, which conceptualizes

entrepreneuring in terms of vision, concrete action, passion, emotion and improvisation (e.g.

Hjorth, Johannisson, & Steyaert, 2003; Johannisson, 2011).

Finally, most studies look into the effect of commercialization on performance (e.g.,

Kallio et al., 2016). To the best of my knowledge, this is one of the very few studies that

investigate the effect of commercialization on evaluation, thereby establishing a link between

the two apparently disparate streams of literature.

41

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Appendix

Figure 1

Two-stage model of commercialization of cricket in India

Note: the broken lines indicate that the increase in the market size with time is non-linear

Market size

Cricket as a commercial artefact

Cricket as a mass market-ready artefact

2008-present 1930-2008 Time

-1930

Cricket as a cultural artefact

54

Table 1

Nationality

Frequency

(Id) Percentage

Cumulative

Percentage

Afghan 2 0.78 0.78

Australian 33 12.79 13.57

Bangladeshi 2 0.78 14.35

Dutch 1 0.39 14.73

English 11 4.26 19.00

Indian 160 62.02 81.01

New Zealander 11 4.26 85.28

South African 20 7.75 93.03

Sri Lankan 4 1.55 94.58

West Indian 14 5.43 100.00

Total 258 100.00

55

Table 2

Variables 1 2 3 4 5 6 7 8 9 10 11 12 13

1. Square-root

base price

1

2. Age 0.230 1

3. Runs 0.341 0.224 1

4. Wickets 0.154 0.141 -0.078 1

5. Catches 0.291 0.173 0.669 0.203 1

6. Specialist -0.035 -0.079 -0.017 -0.133 -0.006 1

7. Sixes 0.346 0.213 0.886 -0.022 0.566 -0.110 1

8. Five wickets 0.039 -0.024 -0.023 0.220 -0.007 -0.028 -0.016 1

9. Indian -0.165 -0.196 -0.008 -0.001 0.048 0.168 -0.081 -0.033 1

10. Entertainment -0.029 -0.028 -0.008 0.004 -0.011 -0.146 -0.028 0.007 -0.004 1

11. Visibility 0.439 0.342 0.432 0.276 0.399 -0.077 0.390 0.060 -0.349 -0.010 1

12. Visibility2 0.488 0.352 0.468 0.277 0.414 -0.061 0.426 0.065 -0.364 -0.005 0.973 1

13. Visibility2 x

Indian

0.122 0.022 0.269 0.169 0.302 0.112 0.154 -0.003 0.775 -0.025 0.237 0.212 1

Variables 1 2 3 4 5 6 7 8 9 10 11 12 13

1. Square-root

final price

1

2. Age 0.224 1

3. Runs 0.512 0.224 1

4. Wickets 0.182 0.141 -0.078 1

5. Catches 0.398 0.173 0.669 0.203 1

6. Specialist -0.083 -0.079 -0.017 -0.133 -0.006 1

7. Sixes 0.470 0.213 0.886 -0.022 0.566 -0.110 1

8. Five wickets 0.055 -0.024 -0.023 0.220 -0.007 -0.028 -0.016 1

9. Indian -0.109 -0.196 -0.008 -0.001 0.048 0.168 -0.081 -0.033 1

10. Entertainment -0.024 -0.028 -0.008 0.004 -0.011 -0.146 -0.028 0.007 -0.004 1

11. Visibility 0.563 0.342 0.432 0.276 0.399 -0.077 0.390 0.060 -0.349 -0.010 1

12. Visibility2 0.615 0.352 0.468 0.277 0.414 -0.061 0.426 0.065 -0.364 -0.005 0.973 1

13. Visibility2 x

Indian

0.260 0.022 0.269 0.169 0.302 0.112 0.154 -0.003 0.775 -0.025 0.237 0.212 1

56

Table 3

Model 1 Model 2 Model 3 Model 4

VARIABLES Square-root

Final Price

Square-root

Final Price

Square-root

Final Price

Square-root

Final Price

Age 67.27*** 35.79 27.41 25.78

(24.47) (23.49) (23.02) (22.87)

Runs 6.041*** 4.545*** 3.370*** 3.218**

(1.237) (1.276) (1.249) (1.254)

Wickets 39.87*** 14.70 4.083 3.625

(14.28) (14.79) (14.48) (14.47)

Catches 66.41** 46.35 44.39 43.29

(33.20) (32.40) (31.87) (31.76)

Specialist (dummy) -207.2 -219.7 -323.4 -314.9

(254.0) (238.9) (235.1) (236.2)

Sixes -21.60 -9.548 -8.321 -4.604

(24.42) (24.13) (23.64) (23.74)

Five Wickets 175.5 140.4 19.29 66.75

(706.1) (694.2) (682.0) (680.0)

Indian (dummy) -395.4* 198.4 460.7** -217.1

(229.7) (235.9) (234.9) (596.1)

Entertainment

(dummy)

-40.09 -36.46 -101.0 -95.70

(189.4) (185.5) (181.1) (181.5)

Visibility 411.8*** -683.3*** -770.4***

(63.05) (204.6) (208.9)

Visibility2 105.8*** 103.9***

(18.02) (18.17)

Visibility2 x Indian 13.62

(10.64)

Constant 2,343*** 506.2 3,094*** 3,901***

(838.6) (914.7) (972.3) (1,024)

Yearly fixed effects Yes Yes Yes Yes

Observations 1,182 1,182 1,182 1,182

Number of Id 258 258 258 258

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

57

Table 4

Model 1 Model 2 Model 3 Model 4

VARIABLES Square-root

Base Price

Square-root

Base Price

Square-root

Base Price

Square-root

Base Price

Age 45.30*** 21.36 14.74 12.38

(17.43) (16.61) (15.83) (15.75)

Runs 5.695*** 3.734*** 2.630** 2.240*

(1.343) (1.278) (1.259) (1.259)

Wickets 57.26*** 28.28 14.74 13.00

(19.08) (17.92) (17.06) (16.83)

Catches 100.1*** 76.97** 82.35*** 81.45***

(31.39) (30.70) (29.86) (29.76)

Specialist (dummy) 61.43 39.01 -91.45 -73.43

(174.0) (165.0) (163.6) (163.7)

Sixes -1.002 13.43 10.41 18.13

(23.24) (22.55) (22.21) (22.38)

Five Wickets 324.6 371.7 274.2 338.2

(669.3) (649.1) (630.8) (629.5)

Indian (dummy) -435.8*** 65.18 294.3* -864.2*

(165.6) (173.1) (171.8) (451.8)

Entertainment

(dummy)

73.49 67.44 14.93 38.92

(165.2) (159.9) (155.1) (155.9)

Visibility 393.5*** -831.5*** -988.6***

(52.37) (212.3) (221.5)

Visibility2 112.9*** 110.9***

(17.58) (17.47)

Visibility2 x Indian 22.36***

(7.855)

Constant 1,826*** -182.5 2,830*** 4,188***

(652.0) (679.6) (841.1) (962.8)

Yearly fixed effects Yes Yes Yes Yes

Observations 1,182 1,182 1,182 1,182

Number of Id 258 258 258 258

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

58

Table 5

2008 - 2014 2015 - 2017

VARIABLES Square-root

Base Price

Square-root

Final Price

Square-root

Base Price

Square-root

Final Price

Age -2.348 1.768 21.49 25.04

(26.23) (27.74) (20.51) (28.98)

Runs 1.199 3.823** 1.583 2.496*

(1.755) (1.814) (1.571) (1.511)

Wickets -6.189 8.196 29.72 13.68

(21.21) (20.35) (20.89) (18.80)

Catches 114.9** 70.17 72.52** 41.90

(47.17) (50.14) (35.55) (34.14)

Specialist (dummy) -203.9 -332.4 32.84 -270.8

(233.0) (263.6) (233.2) (294.9)

Sixes 11.34 -20.84 40.63 15.91

(29.76) (30.95) (32.16) (30.88)

Five Wickets 693.6 907.6 -1,046 -1,522

(687.9) (785.4) (2,453) (1,672)

Indian (dummy) -145.6 131.5 -1,733*** -973.3

(680.9) (699.8) (584.0) (711.9)

Entertainment

(dummy)

-166.5 -174.3 158.9 -211.3

(224.8) (261.5) (209.2) (246.4)

Visibility -952.5*** -851.0** -1,002*** -709.5***

(341.2) (331.6) (209.5) (245.7)

Visibility2 107.7*** 109.0*** 111.9*** 96.54***

(25.54) (27.07) (17.67) (20.74)

Visibility2 x Indian 6.810 12.84 42.90*** 23.97*

(11.74) (12.29) (10.57) (12.98)

Constant 4,457*** 4,922*** 3,676*** 3,442***

(1,485) (1,488) (1,075) (1,307)

Yearly fixed effects Yes Yes Yes Yes

Observations 650 650 532 532

Number of Id 162 162 255 255

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

59

Essay Two

Another Bollywood re-make? The emergence of a new category by borrowing external

categorical codes

Abstract

Categorization studies have stolen the limelight in the domain of organization theory in

recent times. This is driven by the changing market conditions and the emergence of new forms

of organization and organizing, which often gives rise to new categories. However, most

studies in this vein focus on the downstream side of categories. The formative processes of

categories have traditionally received limited scholarly attention. Literature suggests that

borrowing external categorical codes from other domains is a mechanism through which new

categories are created. But the exact nature of the borrowing, that is, which codes are borrowed,

and if the process is random or strategic, is still not clearly understood. I address this gap by

studying the new commercially motivated soccer league in India, called the Indian Super

League (ISL). Econometric analysis of data on player evaluation suggests that the ISL

borrowed its codes from the IPL, and only those codes were borrowed that led to the

commercial success of IPL. The codes have a similar effect on micro-mechanisms like player

evaluation in both the leagues, and I observe that in the ISL, ascriptive factors like a player’s

status matter more in their evaluation after controlling for objective performance. These

findings contribute to the literatures of institutional logics, and categories.

Keywords: Category formation, category codes, borrowing, institutional logics

60

Introduction

The study of categories has experienced a revival in scholarly interest in the last few

decades (Glynn & Navis, 2013; Vergne & Wry, 2014). Categories are groups of entities which

have common or similar physical or material attributes (Carruthers & Stinchcombe, 1999;

Douglas, 1986). Essentially, categories can be visualized as conceptual buckets consisting of

similar elements and help in the understanding organization-environment relationships (Negro,

Hannan, & Rao, 2010). They also provide a cognitive infrastructure that facilitates evaluations

of organizations and their products (Durand & Paolella, 2013). The aspects of category studies

that have received major attention from scholars are categorical codes and categorical

membership, evaluations, the phenomenon of category spanning or straddling and their

consequence on firm performance, and more recently, the mechanisms of formation of new

categories.

Study of categories in organizational studies is important for several reasons. Since

categories provide an instrument for organizational and product evaluation and have a direct

impact on firm outcomes, understanding of the nuances of categories is instrumental for the

understanding of markets. Furthermore, the study of the mechanism of formation of categories

helps to shed light on a broader subject of contemporary interest in management research,

namely, the translation and diffusion of ideas and innovation. A growing number of

contemporary scholars in management agree that translation, variation and adaptation are

intrinsic to the diffusion of ideas, innovation and organizational processes. Some of the notable

works in this vein include research by the school of Scandinavian institutionalism on the travel

of ideas and the translation of innovation (Czarniawska and Sevón, 2005; (Boxenbaum &

Battilana, 2005; Morris & Lancaster, 2006; Sahlin & Wedlin, 2008), the “glocalization” of

organizational forms and practices (Djelic & Sahlin-Andersson, 2006; Drori, Höllerer, &

61

Walgenbach, 2014; Frenkel, 2005) and the adaptation of innovation during their diffusion

(Ansari, Fiss, & Zajac, 2010).

However, categorization studies still suffer from certain limitations. Most studies in this

vein look into already existing categories and the consequents of such categories (Vergne &

Wry, 2014). One of these outcomes is concered with the issue of the “categorical imperative”

(Zuckerman, 1999), where organizations are forced to adhere to the codes of the categories to

which they belong. Deviant organizations run the risk of lower evaluation by their audience

(Hsu, 2006; Kovács and Hannan, 2010). This skewed focus on the consequents of

categorization has resulted in severe limitations in our understanding of the origin or the

formation of categories (Blanchet, 2018). Many recent publications have highlighted this gap

and have called for extensive research in this vein (Corbett et al., 2013; Navis and Glynn, 2013;

Vergne and Wry, 2014; Durand & Khaire, 2017).

A review of the literature on the formation of categories has identified two main

processes through which new categories are formed. These two processes are “category

emergence” and “category creation” respectively (see Durand & Khaire, 2017). Category

emergence happens when a new category is formed through the importation of components

that were exogenous to the main categorical system. Category creation is the process by which

existing components of a category in a market are “rearranged, reinterpreted, and relabeled to

generate new meanings and associations” (Durand & Khaire, 2017: 95). In this process, new

categories emerge from within an existing category system through an iterative process

reinterpreting the components and redefining the boundaries (Casasanto & Lupyan, 2015;

DiMaggio, 1987).

However, the mechanism of “category emergence” (Durand & Khaire, 2017) does not

explain the exact conditions of the importation or borrowing of the external categorical codes

62

that constitute the new category. This limitation gives rise to a myriad of questions related to

the process – whether it is random or strategically motivated and emergent or path dependent.

I address this gap by studying the commercially motivated soccer league in India called the

Indian Super League (ISL). The league was started in 2014 after the immense commercial

success of its cricket counterpart, the Indian Premier League (IPL). Many of the attributes of

ISL are similar to that of the IPL. Overall, I find that the ISL was designed in similar lines with

the IPL, because both the leagues were commercially motivated. The ISL borrowed its codes

from the IPL, and only those codes that led to the commercial success of IPL. The codes have

a similar effect on micro-mechanisms like player evaluation in both the leagues, and I observe

that in the ISL, ascriptive factors like a player’s status matter in their evaluation after

controlling for objective performance. These findings shed light on our understanding of the

borrowing mechanism during the formation of new categories and contributes to the literatures

of institutional logics, and categories. A study of such multi-dimensional nature demands novel

theoretical lenses, which are oftentimes developed by combining and transforming different

theoretical traditions. A review of the extant research on categorization (Vergne & Wry, 2014)

indicates a convergence in institutional logics and category studies leading to the development

of a novel theoretical lens, which I use for this study.

The paper is organized as follows. In the next section, I briefly review the literature and

theories on categories, their legitimation and their formation. After that, I describe the research

setting, the research design, data, and methods. Finally, I conclude by discussing the primary

findings and the contributions.

Theory

What are categories

63

Categories can be defined as “conceptual tools for understanding organization-

environment relationships” (Negro, Hannan, & Rao, 2010: 4). A category is an economic

exchange structure between producers and consumers that is governed by a mutually agreed

upon meaning. The meaning is co-created and attributed by the actors and audiences who use

it (Kennedy, 2003). Category labels are used to describe the core features of the category

(Mervis and Rosch, 1981) which help in creating the identity that set audiences’ expectations

(Hsu and Hannan, 2005; Polos, Hannan and Carroll, 2011). According to Durand and Paolella

(2013:1102), “in the context of markets and organizations, categories provide a cognitive

infrastructure that enables evaluations of organizations and their products, drives expectations,

and leads to material and symbolic exchanges”. Durand & Khaire (2017) posit that categories

group and distinguish entities either in terms of common or similar physical or material

attributes (Carruthers & Stinchcombe, 1999; Douglas, 1986; Zerubavel, 1997) or in a more ad-

hoc fashion (Casasanto and Lupyan, 2015). Categories play a significant role in the way

markets function, since they have a status-ordering influence on markets (DiMaggio, 1987;

Lounsbury and Rao, 2004). An existing market classification usually tackles valuation related

issues through the categorical imperative perspective (Zuckerman, 1999).

New categories lead to the creation of nascent markets, that have been defined as

“business environments in an early stage of formation” (Santos and Eisenhardt, 2009: 644).

Environments under such early stage formation are characterized with uncertainties which arise

because technologies, products or processes are “untested and incompletely understood”

(Tushman and Anderson, 1986: 444). Also, product definitions are unclear or unknown

(Hargadon and Douglas, 2001). However, these ambiguous dynamics and unclear definitions

provide suitable conditions for the emergence of a new market category which could eventually

become a dominant category through the processes of legitimation and diffusion. Thus, it is

extremely important for market participants like incumbent firms, startups, producers,

64

suppliers, intermediaries and others to understand the category formation mechanisms as they

can control, own and influence some newly form categories or design strategies which lead to

the development of new categories where they might command a superior competitive

advantage because of their role in the formation of that category.

According to (Navis and Glynn, 2010), new categories can be created in a number of

different ways. A few of these ways are through new product classes (e.g., Rosa et al., 1999),

new service classes and opening “new worlds” for existing product or service classes (Tushman

and Anderson, 1986: 461). A category is formed when there exist two or more products that

are perceived to be of the same type or close substitutes to each other. The organizations that

produce and supply these products are often grouped together as members of the same market

category (Navis and Glynn, 2010). Such categories have two basic characteristics. First, the

constituent members are included in the category through the adherence to rules or boundaries

pertaining to that particular product, and second, a distinct concept, label, or identity is created,

which highlights the commonalities that link the members of the category to each other (Mervis

and Rosch, 1981). These characteristics constitute the identities for both the category as a

whole and also the constituting organizational members (Navis and Glynn, 2010). A

constituting organization’s identity gravitates around its central, distinctive, and enduring

attributes (e.g., Albert and Whetten, 1985) and its rightful membership in that particular

category (Glynn and Abzug, 2002; Glynn, 2008). The identity of the category develops around

a prototype, i.e., the best representation of what it means to be a member of that category

(Mervis and Rosch, 1981). This expectation of the typical category member contributes in the

development of an identity code (Polos, Hannan, and Carroll, 2011; Hsu and Hannan, 2005)

that is agreed upon by category members and understood by relevant audiences (Romanelli and

Khessina, 2005). Categorical codes influence the performance of organizations, institutions,

and their members. For example, commercialization of academia has changed the codes which

65

govern the category of universities and other educational institutions, and this change has led

to the development of new performance measurement systems for universities and academics

(e.g. Kallio et al., 2016).

Formation of new categories

How do new categories emerge? This question has been instigating the academic

community for several years. Because of the interdisciplinary nature of the research question

and the plethora of actors and factors that result in the formation of new categories, scholars

across disciplines like management and marketing have attempted to solve the puzzle. While

much work has already been done in this vein, the understanding of how new categories emerge

and stick around is far from complete and much work still needs to be done in this vein.

A review of the extant literature uncovers the current state of our understanding of the

formative processes of new categories. Most studies in management research on categories

focus on the after-effects of category formation, that is, the transactions within a category

between participating actors (Durand & Khaire, 2017). The distinct theoretical lenses that have

been used so far to study categorization are the organizational ecology lens, the institutional

lens, and the strategic management lens respectively.

The organizational ecologists focus more on the processes by which category members

come to an agreement on category labels and their content. These processes are usually

engineered by “enthusiasts” who define categorical codes, membership identity criteria and

diffuse those among other members of that category (Hannan et al., 2007: 75). Another way by

which such processes are brought about is through the action of authorities who impose

classification criteria, categories and the corresponding codes. The earlier works by

organizational ecologists are being furthered by current scholars to understand how categories

arise and exist in different niches within the ecosystem (Hannan, 2010).

66

In the institutional view of categories and their emergence, categories are treated as

entities that are given, similar to the ecological perspective. Governed by institutional

isomorphism principles, categories summarize key features of legitimacy that are agreed upon

by market participants (Navis and Glynn, 2010; Schneiberg and Berk, 2010; Zuckerman,

1999). For example, a study of the emergence of industrial classification in the post - Civil War

period found that firms needed to belong to crisp categories as they became institutionalized

(Ruef and Patterson, 2009). Kennedy (2008) highlighted the need for firms of benchmarking

themselves against existing and legitimate rivals to carve out a category and be recognized as

a new category member. Other works (e.g., Jones, Maoret, Massa, and Svejenova, 2012; Wry,

Lounsbury, and Glynn, 2011) also highlight the agentic nature of organizations that are

“disciplined” by categorical systems, both cognitively and normatively (Durand and Khaire,

2017). Furthermore, such organizations tend to individually or collectively reshape category

boundaries and membership conditions and influence key outcomes (Hsu and Grodal, 2015;

Kennedy, Lo, and Lounsbury, 2010; Kim and Jensen, 2011).

The strategic management view puts agency on the front stage (Durand and Khaire,

2017). Several papers in this stream have studied the consequences of category spanning and

bundling (Granqvist et al., 2013; Wry et al., 2014). The primary line of investigation of this

stream of research has been the straddling of firms into opposite categories and the eventual

consequence on firm performance, reputation, or strategic actions (e.g., Vergne, 2012; Wry et

al., 2014). However, in almost all of these studies, categorical systems have been assumed to

preexist and firm actions were assumed to be constrained by the codes of those preexisting

categorical systems. In their seminal paper about French cuisine, Rao et al. (2005) studied the

emergence of the new category of “nouvelle” French cuisine, a branch that separated from the

“classical” cuisine and the eventual blurring of the boundaries between them, that lead to the

hybridization of French cuisine in general. The emergence of the new category of cuisine and

67

the blurring of the boundaries was brought about by star Michelin chefs. It can be argued that

the status of the chefs aided the creation and the acceptance of the new category. In a similar

study, Jones et al. (2012) looked into the conflict within the de novo category of modern

architecture that led to the emergence of modern functional architecture and modern organic

architecture. This conflict was guided purely by conflicts between the two classes of architects

who were guided by competing logics.

A new category is incomplete without a common meaning that is shared and understood

by the different market actors that deal with that category. This attribution of meaning and the

creation of a new category go hand in hand. Khaire and Wadhwani (2010), in their paper on

modern Indian art, find that producers and consumers were not the only parties that shaped the

key constructs and meanings in the discourse defining new categories. Other actors and

intermediaries (art historians, auction houses, critics and museums, for that particular study)

also play a very important role in the process.

A recent review of literature on the formation process by Durand and Khaire (2017)

highlighted two key processes by which new categories are formed. They are category

emergence, and category creation, respectively.

Category Emergence

Category emergence happens when a new category is formed through the importation

of components that were exogenous to the main categorical system. Emergent categories are

formed by new, hard-to-classify (within existing systems) attributes of a good (Durand and

Khaire, 2017). Such processes are usually championed by innovators, which are often startup

firms. In category emergence, physically observable features are imported from other

categories that might be conceptually adjacent to or distant from the category in question. Firms

engaging in category emergence attempt to facilitate “new criteria for product selection that

68

gives them an advantage over rivals in terms of attractiveness and value capture” (Durand and

Khaire, 2017: 94).

Category Creation

Category creation is said to be in force when existing components of a category in a

market are “rearranged, reinterpreted, and relabeled to generate new meanings and

associations” (Durand and Khaire, 2017: 95). In this process, new categories emerge from

within an existing category system through an iterative process reinterpreting the components

and redefining the boundaries (Casasanto and Lupyan, 2015; DiMaggio, 1987). This process

of new category formation highlights the distinctions of the category members by coining new

discourses and framings (Sauder, 2008; Weber et al., 2008).

However, the authors also point out that the two processes are not the only possibilities

of new category formation. They posit that there may exist situations where the two processes

of emergence and creation can operate jointly, either in parallel or in sequence. Sgourev (2016)

highlights the endogeneity issue of category formation and posits that the emergence of new

categories is in a way, path dependent - “Emergence of new categories is conditioned on the

content of pre-existing categories” (Sgourev, 2016; 5). This endogeneity issue is often ignored

by scholars, thereby missing out on some minute, key nuances of the formation of new

categories. The author claims that new categories borrow not only from pre-existing categories,

but also from the key agent promoting the new category, and proposes the mechanism of

“bifurcation”, where a new category bifurcates from an existing category through emergence

of some of the categorical codes as “relational opposites” to the preexisting ones, orchestrated

by the key promoter. The paper studies the emergence of the modern ballet which co exists

with the classical ballet from which it bifurcated.

Legitimacy of a new category

69

Extant literature also posits that legitimacy is extremely important for new categories

since legitimacy has a positive effect on resource availability and wealth creation (Aldrich and

Fiol, 1994; Rosa et al., 1999; Santos and Eisenhardt, 2005). Legitimation is a complex social

process (Fligstein, 1997; Kennedy, 2008). The process involves a wide range of stakeholders

like organizations and prospective resource providers such as investors, analysts, customers,

media, and other interested audiences. All these stakeholders contribute collectively in the

social construction of a category’s meaning and the formation of identities, (Tripsas, 2009).

Extant research offers insights into various aspects of this legitimation process by highlighting

divergent, sometimes even contradictory accounts of the mechanism of legitimation. For

example, on one hand, according to the institutional and organizational ecology view, forces

external to organizations arising from isomorphic pressures (e.g., Deephouse, 1996; Glynn and

Abzug, 2002) and shared expectations of relevant audience groups (Hsu and Hannan, 2005;

Polos, Hannan and Carroll, 2011; Hsu, Hannan and Kocak, 2009) drive legitimacy. On the

other hand, entrepreneurship and organizational identity schools emphasize on the inner

workings or organizations like firm attributes (Albert and Whetten, 1985) and organizational

practices, models, or concepts (e.g., Zimmerman and Zeitz, 2002) as main drivers of

legitimacy. A third, social construction view combines the two and posits that the formation of

a new categories is an active, social project (Fligstein, 1997; Kennedy, 2008; Kennedy, Lo, and

Lounsbury, 2010) that involves the interpretations and actions of both organizations and

relevant audiences.

Many of the theories that emerged from the study of organizations view categorization

as a function of organizational environments (Scott, 1981). These theories predominantly focus

on collective processes to explain organizational phenomena and treat categories as socially

constructed partitions that impart particular meanings to those divided social spaces (Durkheim

and Mauss, 1963). Categorization has a profound impact on identities and characteristics of

70

markets and organizations operating within those markets and affects the social, cultural, and

material resources available to them (Negro et al., 2010). As a result, and to create competitive

advantage for themselves, organizations often put active effort to shape category systems and

the process of categorization. Institutional theorists have worked extensively to understand the

cultural and cognitive processes that influence organizational behavior and firm strategy and

argue that the social and cultural frameworks that organizations are embedded in shape the

behavior and strategies of such organizations (Meyer and Rowan, 1977; DiMaggio and Powell,

1983). Some of the instruments through which such behavior and strategies are shaped and

reshaped are scripts, schemas, rules, and norms (Zucker, 1983; DiMaggio and Powell, 1991).

In this line of research where formation and legitimation of categories is treated as a

function of the external environment, Zuckerman’s (1999, 2000) work was the first to posit

that category systems are taken-for-granted constructs, which have an immense influence on

market behavior and market outcomes. In a study of the financial markets, Zuckerman found

that firms failing to establish themselves as members of financial analysts’ categories were less

likely to attract attention by analysts who specialize in that particular industry. This results in

the firm being less attractive to investors which has negative consequences on the firm’s value

on the stock market and their stock price (Zuckerman, 2004). To avoid such situations of

negative consequences, firms tend to conform to the category codes as understood and agreed

upon by their audience and evaluators (Zuckerman, 2000). This concept was further developed

by Phillips and Zuckerman (2001) into a two-stage model of legitimacy of a category, which

is based on interchanges between a firm and its audience. A firm presents itself as a legitimate

member of a particular category and offers products or services that are pertinent to that

category. The audience members who consume those products or services evaluates the firm

with reference to their adherence to the category codes.

71

As a general phenomenon, firms that are closer to the defining features or codes

representing a particular category perform better than firms that are more distant from such

features, adhere to the codes partially or span across different categories. Acts of categorical

spanning confuse the audience by signaling lower competence in the spanned domains

compared to firms specializing in single categories. Several factors have been posited to

influence such effects, such as the lenience of categories, the presence of multiple audiences

with different and distinct expectations, and the appeal of multiple category membership

(Hannan, 2010; Hsu, 2006; Hsu et al., 2009; Negro, Hannan, and Rao, 2011; Pontikes, 2012).

I argue that because of the legitimacy factor, the borrowing mechanism is not random,

but strategic. When a new category is created by borrowing exogenous codes from other

categories, the borrowed codes are expected to have moderate degrees of congruency with the

codes of the lending category that are important for achieving the objectives of the new

category. To be more precise, if a new category is predominantly driven by commercial

objectives and borrows codes from an adjacent, external category, it will borrow those codes

which led to the commercial success of the lending category. In the specific case of the ISL,

the codes related to the design of the league and the evaluation of the players are expected to

be similar to those of the IPL because both these leagues are commercially motivated.

Research setting – deviation from the traditional

The research is situated in the context of the newly developed commercial soccer league

in India, called the Indian Soccer League (ISL). Even though soccer is an immensely popular

sport in India, it is far behind cricket in terms of popularity. It is viewed by millions in the

country, although only a few regions of the country are known for playing the sport locally.

Several Indian states like West Bengal, Kerala, Maharashtra, and Goa have had semi-

professional derivatives of soccer for decades (Ray, 2014) Soccer in India is governed by the

72

body called the All Indian Football Federation (AIFF), which was founded in 1937. The AIFF

also organizes the natural soccer league (i-league) and various other tournaments like the

Durand Cup and the Super Cup. In 2013, a new kind of soccer league came into being in India

as a commercial derivative of the sport. Although the AIFF governs the league as a whole, the

league was predominantly conceptualized and controlled by a consortium of three major

corporations, Reliance industries, one of India’s biggest industrial conglomerates, IMG, the

global events management company, and Star TV, the owner of multiple global media outlets.

The diffusion of soccer in India has been rather unique. Even though the barriers to

access the sport has historically been low, unlike those to access cricket during the British Raj

(see Appadurai, 1995, 2005; Salve, ), the sport has not been able to match the popularity of

cricket. People play soccer actively in India in several states (Ray, 2014), but not in many

others. This is despite the fact that India had a decent history in the world of soccer in the past.

India came fourth in soccer the 1956 Olympic games, and also had won two Asian Games gold

medals. However, the consumption of soccer in terms of viewership far surpasses these

numbers. Many viewers in India stick to their television screens to watch their heroes like

Rooney, Messi, and Ronaldo in major European soccer leagues like the UEFA Champion’s

League, the Bundesliga, the Premier League and international tournaments like the Euro

Championships and the soccer World Cup.

After the commercial success of the Indian Premier League (IPL), a franchisee-based

cricket league in India, where Bollywood stars and industry leaders invested tremendous

amounts of money to buy teams, it is only normal to predict a similar strategic diversification

in the area of soccer. This is predominantly because of the market-readiness of the sport to be

commercialized, given the millions of views of quality soccer in the country. Adhering to the

same philosophy, the aforementioned three industrial conglomerates got together along with

the AIFF and designed the commercialized avatar of soccer in India, the ISL. The idea was to

73

bring former international stars to India to exploit the market, and to improve the overall quality

of the sport in India. This is in line with the vision to make India a global soccer power and the

ambition to qualify for the 2026 soccer world cup, as mentioned on the ISL website

(https://www.indiansuperleague.com/about-indian-super-league). Accordingly, former

international stars were drafted as marquee players for the league. Some of famous names

included Alessandro del Piero, Fredrick Ljungberg, Luis Garcia, Robert Pires, David

Trezeguet, Nicholas Anelka, and Dimitar Berbatov. Some other famous names like Zico,

Marco Materazzi, Robbie Keane, and Roberto Carlos acted as head coaches of some of the

teams in the league.

The inauguration of the ISL in October 2014 was very much like that of the IPL,

attended by a crowd of 60,000 spectators, along with Bollywood stars like Amitabh Bachchan,

sports celebrities like Sachin Tendulkar, and business tycoons like Nita Ambani, many of

whom were the owners of the participating eight franchisee teams (Law, 2014). This was

probably the first time when soccer fans in India got to enjoy the sport in a safe environment

with their families. The ceremony started with the beats of drums, played by 160 musicians,

followed by performances of popular Bollywood stars like Priyanka Chopra. The opening game

was watched by 74.7 million viewers on television (Ray, 2014 – different article). Furthermore,

in the first year of its inception, ISL became the fourth most attended league after the national

leagues in England (Premier League), Germany (Bundesliga) and Spain (La Liga) (Ray, 2014).

The league was generously promoted on social media too, to keep up with the digital

consumption trends of the contemporary generation.

The analysis

Building on my prior research on the commercialization of cricket in India and the

subsequent impact of commercialization on player evaluation, I analyze the impact of

74

commercialization on soccer and the eventual creation of the new category, which is a

concoction of traditional soccer, entertainment, and business. In particular, I examine the effect

of commercialization of soccer on player evaluations in the context of the ISL. This analysis

also sheds light on the process of borrowing of categorical codes when new categories are

formed (see Durand & Khaire, 2017). I argue that the commercialization of soccer in India and

the eventual creation of the ISL was strategically motivated. The league was very similar in

design to the IPL and hence, I argue that the evaluation of players in the ISL would also adapt

similar trends as I have seen in the IPL. In other words, ascriptive factors like status will play

significant role in evaluation, after controlling for objective factors.

The unbalanced panel dataset consists of 600 observations for 367 soccer players in the

ISL for three seasons, 2016, 2017 and 2018. Although the ISL started in 2014, the governing

bodies did not start an evaluation system before 2016. Hence, I have only considered the three

seasons between the years 2016 and 2018 for the purpose of this study. I have scraped the

performance related data, the control variables, and the dependent variable from the official

ISL website. I have also collected data regarding FIFA rankings from FIFA’s official website

for the respective years.

Control variables

The number of matches that a player has played may have an effect on their

performance evaluation. On the one hand, the number of matches played can be deemed as a

proxy for experience. The more experienced a player is, the better he is expected to be because

of a learning-curve effect, where performance improves because of repetitions of the same

work over time, where the underlying technology remains unchanged (Rothaermel, 2015). On

the other hand, one can argue that if a player gets more matches, it is more likely that he will

be able to demonstrate his skills and quality more appropriately, than a player who gets only

75

limited chances to play. To control for that factor, I have taken the number of matches played

by the players in the ISL as a measure of their experience.

Furthermore, a player’s role in the sport may have an effect on their performance. In

soccer, four different player roles can exist. The goalkeepers are predominantly entrusted with

the duty of saving attempts to score goals by the opponent team. Defenders usually play in the

defensive third of the playing pitch, with occasional exceptions, and their main duties are to

defend against the opponent team and prevent them from scoring goals. Midfielder usually

occupy the middle-third of the pitch and assume the role of the playmakers. They also act as

bridges between the defenders and the forwards. Finally, there are the forwards, who usually

play in the attacking-third of the pitch and their primarily responsibility is to score goals for

their teams. I have created dummy variables for the positions Midfielder (MF) and Forward

(F) and have assigned them the value 1 or 0 accordingly. The roles for every player in the ISL

can be obtained from the official website. In terms of roles, the goalkeepers are the most

different from other three roles, and hence I have not considered the goalkeepers for this

analysis. I have used the two dummy variables (MF and F) in my models to control for any

effect that the role of a player might have in their evaluation.

Independent variables

The quality of the players in the aforementioned different roles can be measured by

different attributes. In the absence of a composite measure for performance or quality for the

three different roles, I have considered some common attributes for all the roles as indicators

of quality.

Goals: In soccer, the number of goals scored by a player is an indication of how good

they are. Even though the forwards are the ones who are expected to be experts in scoring goals,

many midfielders and defenders are also famous for scoring many goals for their teams and

76

helping them win. Hence, I have created a variable to indicate the number of goals each player

has scored in each season of the league.

Passing accuracy: Soccer players play by passing the ball around between them. The

number of passes that a player plays, determines their centrality and importance in the team.

However, I argue that the accuracy of the passes played is a better indicator of the importance

or centrality of the players, and subsequently, their quality. Accordingly, I have created a

variable to capture this metric, and have used it as an explanatory variable in my models.

Tackles: In order to prevent the opponent team from scoring goals, players need to

engage in defensive play and one instrument to prevent the opponent from attacking and

scoring goals is to tackle. Defenders are known to tackle more, but players in other roles also

do a lot of tackling during the game. Hence, I have created a variable to capture the number of

tackles that a player has done in each season of the league.

Status: Status is the prestige attributed to an entity as a result of its occupying a

particular position in a social rank (Lynn, Podolny and Tao, 2009; Jensen & Roy, 2008;

Washington & Zajac, 2005). Others define it as an indicator of the perceived quality of a

product relative to the perceived quality of other products (Podolny, 1993). In other words,

status and quality are related. It would be interesting to understand if status of the soccer players

in the ISL have any influence on their evaluation, after controlling for their objective

performance. If the status variable is significant, then it can be argued that the ISL borrowed

similar codes for evaluation from IPL. Such a finding will enrich our understanding of the

borrowing mechanism during category formation.

Dependent variable

Since the 2016 season of the ISL, the governing body started giving every player a

rating at the end of the league and ranked the players according to that rating. This rating is a

77

expression of the player’s performance evaluation by the governing body of the ISL. I created

a variable to capture this metric and is the dependent variable for my analysis.

Hausman test (p = 0.08) indicates that a random effects analysis is better suited for the

analysis. Accordingly, I conduct random effects panel regression analysis on the data.

Results and discussion

The bivariate correlation between the variables used in the analysis are presented in

Table 1. From the correlation coefficients, I find no indication of any major multicollinearity

problem in the models.

---------------------------------------

Insert Table 1 about here

---------------------------------------

Findings of the panel regression analysis are reported in Table 2. Model 1 is treated as

a base model with only the control variables of the number of matches played and the position

dummies (MF and F). All the three performance related predictor variables (goals scored,

passing accuracy, and number of tackles) are added to the baseline model in Model 2. Model

3 includes the status variable. There are very close similarities between the design of the ISL

and that of the commercialized avatar of cricket in India, the IPL. I argue that the status of

players in the ISL will have similar effect as that of the players’ visibility in the IPL.

Accordingly, I suspect that the relationship between evaluation and status in the ISL is not

linear but quadratic. To test this, I include an additional status variable in Model 4. This variable

is a squared version of the status variable that I use in Model 3.

---------------------------------------

Insert Table 2 about here

---------------------------------------

Interestingly, in Model 1 and Model 2, I find that the experience variable (matches) and

the performance variables (goals, passing accuracy, and tackles) are the significant predictors

78

of a player’s evaluation score. This is expected because the sport of soccer is traditionally

governed by athletic logics, in which superior performance leads to better evaluation.

In Model 3, the status variable is negative and significant (z = -3.86, p = 0.000). This

means that status is a significant predictor of evaluation score, and a lower FIFA rank fetches

higher evaluation. This might apparently seem contradictory. However, a lower FIFA rank

means higher status and vice versa. Accordingly, I conclude that similar to the IPL, in the ISL,

ascriptive factors like a player’s status is important in determining a player’s value, after

controlling for objective performance. In Model 4, the squared version of the status variable is

positive and significant (z = 3.81, p = 0.000). This confirms the non linear nature of the

relationship between status and evaluation.

Overall, the results support the assumption that the design of the ISL is very similar to

that of the IPL. I argue that the similarity in design is influenced by the commercial success of

the IPL and is deliberate. Thus, the new category of commercialized soccer in India borrowed

its codes from the commercialized avatar of cricket. The findings shed light on the borrowing

mechanism when new categories are formed (see Durand & Khaire, 2017).

Limitation (status variable)

The analysis is subject to a minor limitation regarding the operationalization of the

status variable. Status has been defined in the literature as the perceived quality relative to

competitors (Podolny, 1993). Audiences develop a perception of status and a status-based

hierarchy by observing the quality of the artefact in question and also the status of its affiliations

(Podolny, 2005). In other words, for a soccer player, a perception of status can be developed

by observing his quality and performance, and also his affiliations, which could be his past and

present clubs, and also his country. A player who plays for a high-status club like Real Madrid

or Barcelona, is usually perceived to be a good quality player and is usually given a higher

79

status. A similar status assignment happens for players who come from countries that have

better FIFA ranks. FIFA assigns a rank to every soccer playing nation based on a points-based

system. The lower the rank, the higher is the perceived status of that nation. For example, a

country whose FIFA rank is 1, is perceived to be of higher status related to soccer with respect

to a country whose FIFA rank is 50. Accordingly, soccer players who belong to a lower FIFA-

ranked country, is believed to be of higher status. This is also validated by the management

literature’s conceptualization of status as the attribution of prestige to an entity as a result of its

occupying a particular position in social rank (Jensen & Roy, 2008; Podolny, 1993;

Washington & Zajac, 2005). Accordingly, for the current analysis, I have operationalized status

of the soccer players at the ISL by the FIFA rank of their respective nations for the particular

years. However, socio-anthropologist Ralph Linton developed the concept of achieved status

and ascribed status. In Linton’s terms, achieved status is linked with performance and abilities

and is attributed to individuals who fulfil the criteria of “requiring special qualities” and “open

to individual achievement” (Linton, 1936). Therefore, part of a player’s status is a consequence

of his performance. Accordingly, a better operationalization of status in this case would have

been a residualized measure of FIFA rank. A player’s performance or quality is also measured

by his market value, or his remuneration. Accordingly, the residuals after regressing the FIFA

rank of a player’s country on his remuneration would have measured status in a much better

manner. The literature also supports this kind of residualized measure of status (e.g. Castellucci

& Ertug, 2010). However, data regarding the salaries of most of the ISL players are not

available publicly. Furthermore, some of the high-status players have already retired from

active soccer and do not earn regular salaries. Considering all these factors, I argue that my

operationalization of status is the best possible, given the existing limitations.

Conclusion

80

The paper sheds light on the mechanisms of new category formation through a study of

the performance evaluation of soccer players at a newly created commercial soccer league in

India called the Indian Super League (ISL). The ISL is not just a sporting event, but it is a

concoction of sports, entertainment, and business, just like its cricket counterpart, the Indian

Premier League (IPL). The ISL was started in 2014, after the commercial success of the IPL

business model, and the primary investors in the ISL came from sports (soccer and cricket),

Bollywood, and Industry (finance, conglomerates, and media and entertainment). Table 3

provides the details of the ownership of the clubs in the first season of the league in 2014.

--------------------------------------

Insert Table 3 about here

--------------------------------------

I posit that after the commercial success of the IPL, it was only obvious that the

promoters would look to achieve similar feat in another domain. Soccer, being the second most

watched sport in India, was a natural choice. The commercialization of soccer followed the

same path as cricket did, instigated by similar participations from industry and Bollywood.

Many of the Bollywood stars who missed out in the bidding process for owning clubs in the

IPL used the opportunity to enter the new arena of sportainment through the ISL. They brought

with them their own logics, very much like they did in the IPL, and eventually, gave rise to a

new category of soccer, which runs parallel to the national soccer league (i-league) in India.

The new category of soccer was created by borrowing codes from the entertainment and the

business worlds, and I have shown that these new codes have had a similar effect on player

evaluation as they had in the IPL. Hence, I argue that the codes that were borrowed from

Bollywood and the industry, were very similar to those that were borrowed from the same

fields in cricket.

It can be concluded that the ISL was designed in similar lines with the IPL, because

both the leagues were commercially motivated. The ISL borrowed its codes from the IPL, and

81

only those codes that led to the commercial success of IPL. The codes have a similar effect on

micro-mechanisms like player evaluation in both the leagues, and I observe that in the ISL,

ascriptive factors like a player’s status matter in their evaluation after controlling for objective

performance. These findings shed light on our understanding of the borrowing mechanism

during the formation of new categories and contributes to the literatures of institutional logics,

and categories.

82

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Appendix

Table 1

1 2 3 4 5 6 7 8 9

Player Rating 1

Matches 0.73 1

Forward (dummy) 0 -0.03 1

Mid-fielder (dummy) 0.02 0.03 -0.45 1

Goals 0.5 0.4 0.35 -0.03 1

PAC 0.21 0.12 -0.44 0.07 -0.17 1

Tackles 0.52 0.69 -0.27 0.08 0.06 0.25 1

FIFA Rank -0.37 -0.28 -0.13 0.01 -0.27 -0.16 -0.16 1

(FIFA Rank)2 -0.34 -0.29 -0.14 0.01 -0.25 -0.13 -0.18 0.96 1

Table 2

Model 1 Model 2 Model 3 Model 4

VARIABLES Player Rating Player Rating Player Rating Player Rating

Matches 0.113*** 0.0786*** 0.0752*** 0.0760***

(0.00456) (0.00657) (0.00655) (0.00648)

Forward 0.0625 0.0284 -0.0291 -0.0157

(Position dummy) (0.0752) (0.0811) (0.0810) (0.0802)

Mid-fielder 0.0238 -0.00119 -0.0176 -0.0142

(Position dummy) (0.0618) (0.0566) (0.0556) (0.0549)

Goals scored 0.131*** 0.125*** 0.121***

(0.0130) (0.0129) (0.0128)

Passing accuracy 0.0130*** 0.0111*** 0.0103***

(0.00218) (0.00221) (0.00219)

Tackles 0.00496*** 0.00502*** 0.00552***

(0.00192) (0.00189) (0.00187)

FIFA rank -0.00193*** -0.00763***

(0.000502) (0.00158)

(FIFA rank)2 3.97e-05***

(1.04e-05)

Constant 5.208*** 4.487*** 4.816*** 4.949***

(0.0672) (0.164) (0.183) (0.185)

R2 (overall) 0.5307 0.6208 0.6326 0.6406

Observations 600 600 600 600

Number of Id 376 376 376 376

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

92

Table 3

Team Name Owner(s) Industries Represented

Atletico de Kolkata Sourav Ganguly

Harshavardhan Neotia

Sanjeev Goenka

Atletico de Madrid

Sports (cricket)

Construction

Conglomerate

Sports (soccer)

Chennaiyin F.C. Abhishek Bachchan

MS Dhoni

Bollywood

Sports (cricket)

Delhi Dynamos Sameer Manchanda Media and entertainment

F.C. Goa Venugopal Dhoot

Dattaraj Salgaokar

Shrinivas Dempo

Home appliances

Sports (soccer)

Sports (soccer)

Kerala Blasters Sachin Tendulkar

PVP Ventures

Sports (cricket)

Media and entertainment

Mumbai City Ranbir Kapoor Bollywood

North East United John Abraham

Shillong Lajong F.C.

Bollywood

Sports (soccer)

Pune City Salman Khan

Kapil Wadhawan

Dheeraj Wadhawan

Bollywood

Finance

Finance

93

Essay Three

Doing “good-work”: Key differences between managers and entrepreneurs with respect

to ethical decision-making in innovation projects - a responsible innovation and

effectuation approach

Abstract

Innovation, or commercialized invention, is a key driver of the economic performance

of firms and the development of national economies. However, many innovation projects raise

serious ethical questions which must be addressed appropriately to minimize the negative

impacts of such innovation. Extant research has paid limited attention to how such ethical

questions are handled by relevant stakeholders. I address this gap by drawing on the concepts

of “responsible innovation” and “effectuation” with an aim to understand the key differences

between managers and entrepreneurs with respect to ethical decision making. This would help

us understand how the principles of sustainability and responsibility are applied and what

practices reduce the potential negative impacts in radical innovation projects.

Keywords: Responsible innovation, governance, decision-making, effectuation

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“We need to move forward on artificial intelligence development, but we also need to be

mindful of its very real dangers.” – Stephen Hawking, November 2017

Introduction

Innovation has remained at the center of managerial and scholarly attention for a while

now. Many definitions of innovation have been proposed over the years, like “…any idea,

practice, or material artifact perceived to be new by the relevant unit of adoption.” (Zaltman,

Duncan, & Holbek, 1973, p. 10), “…an invention which has reached market introduction in

the case of a new product, or first used in a production process, in the case of a process

innovation.” (Utterback, 1971, p. 77), and “Innovation = theoretical conception + technical

invention + commercial exploitation” (Trott, 2012, p. 15). For this paper, I draw on the

common elements of the aforementioned definitions and conceptualize innovation as

commercialized invention. Innovation is often thought to be one of the key drivers of the

economic performance of a firm and the development of an economy as a whole. The initial

typology of innovation was developed in the 1990s (Henderson & Clark, 1990). Since then,

scholars have investigated the strategic implication of the different types of innovation. One

particular kind of innovation has managed to draw most of the attention from scholars and

managers alike – radical innovation, because of its potential for resulting in greater returns on

investments (e.g. Chaney et al., 1991). Radical innovation imbues novelty across two

dimensions – the technological dimension and the consumer dimension. However,

technological novelty often plays a big role in evaluation and adoption by consumers (Veryzer,

1998). Subsequently, I adopt the definition is radical innovation as “a new product or service,

which requires considerable change in customer behavior, is perceived as offering

substantially enhanced benefits and is also technologically new” (Sandberg, 2008: 56).

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Many of the contemporary radical innovations raise several questions on ethical grounds.

One salient example is that of Artificial Intelligence (AI). AI has gained so much prominence

that experts believe that it will be in the mainstream of many organizational activities in the

future. Many present-day organizations have elaborate strategies for incorporating AI in their

functions. However, AI raises several moral and ethical questions too. AI has been projected

to replace many jobs that are performed by humans today. This may have serious implications

in the socio-economic design of the future. Also, the big data systems store and mine personal

information to an extent that has made people uncomfortable with regards to breaching their

privacy. The recent frenzy about the role of Cambridge Analytica in the US presidential

elections is a salient example of consumer data can be mined and used to manipulate human

behavior. So severe are the concerns regarding the usage of AI, that governments have started

setting up ethics councils to keep an eye on such usage1.

These ethical dimensions of AI and other radical innovations can be linked with the various

antecedents and consequents of such innovations, that is, what conditions lead to the

development of such innovations, and how those innovations are used in organizational and

social contexts. The antecedents can be broadly classified into behavioral, cognitive and

structural veins. The behavioral stream looks into the effects of different practices (e.g.

knowledge brokering) of entrepreneurs and managers on firm performance (e.g. Hsu & Lim,

2014). Scholars exploring the structural antecedents study the categorical imperative – the

pressure on firms from their audience to adhere to norms and practices associated with existing

innovation or categories (e.g. Zuckerman, 1999) and the effect of organizational and network

structure on innovation (e.g. Argyres & Silverman, 2004; Reitzig & Sorenson, 2013; Cattani

& Ferriani, 2008). The cognitive stream, which is centered around the decision-making aspect

of innovation, is probably the broadest of the three antecedents. Innovation entails various

1 https://govinsider.asia/innovation/singapore-sets-ai-ethics-council/

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kinds of decisions at all organizational levels – individual, group, and firm. Previous works in

this vein have primarily looked into the different levels of decision making and their suitability

under different conditions (e.g. Csaszar & Eggers, 2013), competing technologies and the

implications of decisions to invest in either one or a combination of such competing

technologies (e.g. Eggers, 2012) and the effects of context (eg. Shepherd & Rudd 2014),

rhetoric (e.g. Hoefer & Green, 2016) and intuition (e.g. Khatri & Ng, 2000) on strategic

decision making, and the impacts of those decisions. The consequents of innovation that have

received the lion’s share of scholarly attention are firm performance (e.g. Hsu & Lim, 2014)

and the attributes of the innovation artefacts like timing of entry and dominant design (e.g.

Suarez et al., 2015).

Most decisions regarding radical innovation are made while keeping commercial objectives

in mind. Some of these decisions are regarding which innovations firms should pursue and lead

to the phenomena of commission and omission errors (e.g. Garud, Nayyar & Shapira, 1997;

Csaszar, 2012). Other decisions are regarding external market conditions, such as timing of

entry in a market (e.g. Suarez et al., 2015). Still other veins of work in this regard have indulged

in a micro-level analysis of speculative decision making and have concluded that phenomenon

like the “emotional oracle effect”, where individuals who have higher trust in their feelings,

can predict the outcome of future events better than others who have lower trust in their feelings

(Pham et al., 2012).

I argue that the ethical questions of such radical innovations have largely been overlooked

by extant research, albeit identifying the importance of such ethical questions. Only a handful

of scholars like Nathan (2015) have attempted to develop a process model for understanding

the governance of such innovations. Nathan’s model focuses on the various stakeholders’

perspective on ethical grounds. I acknowledge the novel work that Nathan and others have

started in this vein but argue that initial models like that of Nathan are limited in explaining

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how the ethical questions of radical innovation are handled because of their limited scope and

focus. I address this gap in research by comparing managerial and entrepreneurial decision-

making characteristics with respect to ethical issues in innovation projects. To this end, I build

on the concepts of responsible innovation and effectuation to understand the key differences

between entrepreneurial and managerial decision-making with respect to the ethical

dimensions of innovation.

Responsible innovation is defined as “taking care of the future through collective

stewardship of science and innovation in the present” (Stilgoe, Owen, & Macnaghten, 2013: p.

1570). It is alleged that responsible innovations are technically superior and socially beneficial

and are very similar to the concept of “good work” (Gardner, Csikszentmihalyi, & Damon,

2002). Innovation environments are often influenced by agency issues, which, in highly

uncertain conditions, are sources from which salient ethical questions that innovators must

address, arise. I intend to contribute to this stream of the literature by studying various decision-

making mechanisms in selected innovation projects, that represent “good work” or responsible

innovation. The broad objectives of this project are:

(1) To understand how innovation projects that raise significant ethical questions regarding

their features, potential use, and future impact on society, are governed.

(2) To understand how those governance mechanisms differ for managers and

entrepreneurs.

Factors influencing innovation choices

Research suggests that the general innovation life-cycle is guided by the evolutionary

processes of variation, selection and retention (Baum & McKelvey, 1999; Lovas & Ghoshal,

2000; Zollo & Winter, 2002). The two dominant processes through which firms build their

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innovation portfolio are “top-down”, which are deliberated by the choices of top managers

(McGrath, 1997; Adner & Levinthal, 2004) and “bottom-up”, which emerge from the strategic

response to market conditions by middle managers and other organizational members

(Burgelman, 1983). The selection process involves choosing one or more innovations from the

generated portfolio and developing them further with commercial objectives in mind (Knudsen

& Levinthal, 2007; Kapoor & Klueter, 2015). The mechanisms of this selection process are

still unclear and warrants further scholarly attention.

One of the suggested mechanisms of selection is that of knowledge brokering. The

brokering process involves “the ability to effectively apply knowledge from one technical

domain to innovate in another” (Hsu & Lim, 2014, p.1). It has been shown that founders’ initial

modes of venture ideation with respect to the adoption of brokering has a substantial impact on

organizational innovation outcomes. Moderate extents of brokering improve a firm’s

innovation performance, whereas too little or too prolonged brokering are not that fruitful.

Firms engaging in knowledge brokering perform better than non-brokers, ceteris paribus. The

non-brokers engage in activities like hiring external expertise to mitigate the performance lag

resulting from not engaging in knowledge brokering at the initial stages.

Structures of organizational and that of the social networks in which the firms are

embedded also have an effect on innovation potential and choices. The core-periphery model

of creativity puts forward the idea that the of origin of radical innovation is more probable in

firms that operate in the periphery of social networks and their diffusion is facilitated by the

firms located in the core of such networks (Cattani & Ferriani, 2008). The core-periphery

model is also instrumental in the explanation of the emergence of business eco-systems and

platforms around certain technology. The peripheral firms are relatively less bounded by the

demands of institutional isomorphism and hence are more prone to come up with radically

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innovative ideas. Whereas, the cohesive core facilitates information sharing because of the

direct connections between the participants in the core (Coleman, 1994; Burt, 1995).

Firm’s decisions regarding which innovations to pursue also depend on the pressures

they face from their consumers who are also their biggest critiques. Firms face institutional

pressure from evaluators like customers and critiques to stick to norms and attributes of

existing, accepted innovations. Failure to do so attracts negative evaluation and penalties from

their consumers and evaluators – a phenomenon known as the “categorical imperative”

(Zuckerman, 1999).

Strategy literature in the last few decades has focused on two broad areas in strategy –

content, and process respectively (Rajagopalan et al., 1993). However, until about a couple of

decades ago, the literature was heavily skewed towards strategy content (Rajagopalan et al,

1993). The authors posit that the content researchers benefited from the existence of sound

theoretical framings and integrative models (e.g. Ansoff, 1965; Andrews, 1971; Hofer &

Schendel, 1978; and Porter, 1980) form early on, which had made their lives a little easier than

process researchers. On one hand, these models provided a common and widely-understood

vocabulary to content researchers, while on the other, they also provided a general sense of

direction on conceptual and empirical grounds. In contrast, the process researchers were

severely handicapped by the absence of such resources, which resulted in limited conceptual

and empirical works in this vein. Process scholars also faced challenges related to the

identification and the measurement of commensurate process variables.

However, since the latter half of 1980, process research has experienced a renewed

vitality and has uncovered intriguing complexities in the domain. This resurgence has also

opened doors for studying interrelationships between content and processes (Huff & Reger,

1987). Scholars like Mintzberg also recognized the salience of research in strategy processes,

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which is expressed in the quote: “More research is required on the process of strategy formation

to complement the extensive work currently taking place on the content of strategies”

(Mintzberg & Waters, 1985, p. 269).

The domain of strategy processes includes a plethora of issues, decision making being

one of the more salient topics. Decision making attempts to understand how strategic decisions

are made in organizations and is an extremely complex subdomain of strategy processes

because of the layers of complexity added by context and contingency, and the number of

stakeholders involved in the decision-making process. However, decision-making in inherently

associated with every possible antecedent of processes, like innovation and has substantial

impact on the consequents of processes like economic performance of firms.

Rajagopalan et al. (1993) posit that various strategic decision models differ with each

other in various respects. However, almost all such decision models share some commonality

along three key dimensions. First, organizational environmental attributes like complexity and

uncertainty influence the mechanisms, characteristics, and outcomes of strategic decisions.

Second, strategic decisions are influenced by endogeneity in various degrees. Current strategic

decisions are often reflections of past strategies, past performance, and organizational structure

and personal characteristics of the decision-maker. Finally, even within a single organization,

the decision-making process for different projects and contexts, like top management teams,

strategic-decision specific characteristics, and firm characteristics, may vary because of

differences in various decision-making factors attributable to factors related to resource and

capabilities.

The decision-making stream is primarily influenced by three sets of factors – structure,

knowledge and environment (Csaszar & Eggers, 2013). Decision-making can be either

individual or collective. In both cases, if decision makers behaved rationally, they would be

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more prone to assessing the present and future values of all the available innovation options

before making a choice. This would result in the retention of only those innovation options that

create value (McGrath, 1997; Zardkoohi, 2004; Bessen, 2008). However, the behavioral theory

of the firm indicates that decision makers are boundedly rational (Cyert & March, 1963;

Barnett, 2008) and, hence, display biases in decision-making. Csaszar & Eggers (2013) posit

that scholarly focus on information aggregation with respect to organizational decision making

is a recent phenomenon. This is driven by the fact that group decision making is a much closer

representation of organizational decision making, unless the concerned firm is a one-person

proprietorship. The authors evaluate different modes of group decision making like delegation

to experts, majority voting, and averaging of opinions. They find that delegation is the most

effective structure “when there is diversity of expertise, when accurate delegation is possible,

and when there is a good fit between the firm’s knowledge and the knowledge required by the

environment.” (Csaszar & Eggert, 2013, p.1). I argue that innovation related decisions are

likely to be influenced by the type, the expertise and the set of values espoused by the parities

to which such decisions are delegated.

A recent review of the literature on strategic decision making (Shepherd & Rudd, 2014)

highlight that strategic decisions are ill-structured, nonroutine, uncertain and pervasive.

Furthermore, such decisions entail a significant financial outlay, and have profound impact on

organizational performance (Eisenhardt and Zbaracki 1992; Mintzberg et al. 1976). Shepherd

& Rudd (2014) also highlight the importance of contextual factors like the top management

team, characteristics of the decisions, external factors and firm characteristics on the effects of

decision making. Such contextual factors also influence organizational choice of innovations.

Other works in the domain of decision making have evaluated the influence of heuristics and

biases (Busenitz & Barney, 1997), timing of commitment to a particular technology (Eggers,

2012, 2014), the role of rhetoric (Hoefer & Green, 2016), and intuition (Khatri & Ng, 2000).

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Scholars have also looked into the effect of trust in feelings on the outcome of decision

making. Pham et al. (2012) found that individuals who have higher trust in their feelings can

predict the outcomes of future events better than individuals with lower trust in their feelings.

The authors call the effect the “emotional oracle effect” and such factors can also influence the

outcome of innovation choices. It can be reasonably argued that managers and decision makers

who have higher trust in their abilities and awareness, would be better at picking the “winners”

more effectively from a given choice set of innovations.

However, the question of how decisions are made by firms about innovations that raise

significant ethical questions regarding their features, potential use, and future impact on society

and how those decision-making mechanisms vary from the ones where the concerned

innovations are more commercially motivated, still remain underexplored.

Responsible innovation and “good work”

Responsible innovation (RI) has been defined as “taking care of the future through

collective stewardship of science and innovation in the present” (Stilgoe, Owen, &

Macnaghten, 2013: p. 1570). The subtle ethical dimension in the aforementioned definition is

embedded in the uncertainties arising out of the future impact of current actions. Research has

already established that a firm’s innovation environment and context is characterized by

uncertainties. Pandza & Ellwood (2013) posit that in situations, where institutional forces put

familiar regulations and protocols in place in a firm’s operating environment, and where there

is a clear trust and widely held agreement and belief in the innovation process of a given field

(i.e. under conditions of low uncertainty), there is little worry or discomfort with any ethical

concerns when innovating. In contrast, when innovation takes place in a context that is

relatively nascent, where there is little to no regulation, and where there are little or no widely

held and shared beliefs in appropriate action (i.e. under conditions of high uncertainty), then

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innovators are often faced with substantial ethical dilemmas. These ethical dilemmas are

reflected in the form of greater contemplations about the unintended consequences of

innovating with a new technology. For example, some artificial intelligence and machine

learning technologies collect lots of personal information from consumers, and in doing so,

“coerce” consumers into making certain choices, a phenomenon that raises obvious questions

on ethical grounds.

The inevitable uncertainties that are at the core of any technological change, in conjunction

with the absence of unambiguous rules, protocols, and norms for steering firm actions, and the

overarching question of ethical responsibility, call for the involvement of agency in building

nascent structures. Agency is inherently embedded in any organizational structure and

capability. In order to better understand the institutional process of "responsible innovation"

scholars need to investigate the nature of "virtue ethics", that is, the relationship between

strategic, ethical and habitual agency (Pandza & Ellwood, 2013).

One salient framework that helps us understand the nature of virtue ethics in RI was

proposed by Owen et al. (2013). The framework includes four dimensions for a RI framework.

The first dimension is termed as “anticipatory” and it deals with “describing and analyzing

those intended and potentially unintended impacts that might arise, be these economic, social,

environmental, or otherwise.” (Owen et al., 2013: 38). The second dimension is “reflective”

and is about reflecting on all the underlying purposes, motivations, and potential impacts of an

innovation and contemplating on the known and the unknown of the concerned innovation.

The third dimension is termed as “inclusively deliberate” and is about “inclusively opening up

visions, purposes, questions, and dilemmas to broad, collective deliberation through processes

of dialogue, engagement, and debate, inviting and listening to wider perspectives from publics

and diverse stakeholders.” The fourth and the final dimension is called “responsive” and is

used to set the direction and have an influence on the subsequent trajectory and pace of

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innovation projects. Such influence is expected to be achieved through effective mechanisms

of participatory and anticipatory governance by using the collective process of reflexivity

(Owen et al., 2013). These four dimensions are expected to complement each other, and work

in an integrated manner to result in responsible innovation.

Scholars have also attempted to develop a typology of work to understand what constitutes

“good work” (Gardner, Csikszentmihalyi, & Damon, 2002). According to the authors, any

work can be characterized by two dimensions – technical excellence and meaningfulness. Such

characterization gives rise to different typologies of work. A work is considered to be excellent,

if it has achieved the highest possible technical superiority and quality. Engaging work, on the

other hand, is personally meaningful, something that the innovator truly believes in. Ethical

work creates value not only for the concerned innovator, but also for others in the society and

are socially responsible (i.e. it also positively impacts society at large).

Building on this concept of “good”, ethical work, I argue that any innovation can be

simultaneously technically excellent, personally meaningful, and socially ethical in the way it

creates values for society as a whole. Essentially, I posit that “good work” and “responsible

innovation” are very similar, if not the same, and that similar ethical dimensions govern the

decision-making concerning such innovations.

Nathan’s model of ethical governance and its limitations

Nathan (2015) attempted to develop a model for ethical governance of innovation projects

by building on the previously disjoint streams of literatures on innovation and ethics. He

addressed the gap in previous literature on RI, where scholars had attempted to address the

need to incorporate ethics and moral standards within the scope of RI (Pavie et al., 2014; Owen

et al., 2013), but had fallen short in explaining how such a framework moderates the decision-

making processes of various stakeholders in innovation projects. Nathan’s main contention was

105

that the extant innovation models were linear and consisted of three distinct stages of input,

throughput, and output respectively, but failed to integrate the principles of ethics or RI.

One of the challenges of the linear process model of governance is that an innovation

process is assumed to have a beginning and an end, and therefore, the responsibilities of the

salient stakeholders are also assumed to end with the ending of the innovation process. Nathan

(2015) argues that such a view of the innovation process and the corresponding stakeholder

responsibilities is limited and proposes a circular process model for the governance of RI

projects, as depicted in Figure 1.

--------------------------------------

Insert Figure 1 about here

--------------------------------------

The proposed model consists of five stages – namely, search, select, implement, capture,

and evaluate. The model also considers the value judgement of both the internal and the

external stakeholders and their networks. The evaluation phase explicitly signifies the ethical

nature of evaluation. Furthermore, the phases are not linearly progressive, but can regress

depending on the decision made by the stakeholders in each phase. Managers are expected to

engage in extensive dialogues and deliberations with various stakeholders to address the

potential ethical impacts in each stage by understanding their interests, rights, duties,

responsibilities, ethical concerns and dilemmas (Nathan, 2015).

A view of Nathan’s model through the strategic decision-making lens makes us realize that

only the first three steps of the model involve strategic decision making. These steps are search,

select, and implement respectively. The remaining two stages of the model, namely capture,

and evaluate predominantly focuses on action rather than on strategic decision. Combining the

aforementioned four dimensions of RI with the first three stages of Nathan’s model, I argue

106

that the first stage (search) corresponds to the anticipatory and the reflective dimensions of RI.

The second stage (select) corresponds to deliberative dimension, and the third stage

(implement) corresponds to the responsive dimension of the RI framework. This kind of

linkage is apparent from the definitions and the explanations of the stages and the dimensions

as enunciated earlier. The combination of the different stages of Nathan’s model and the

dimensions of RI can be conceptually represented by the figure below:

------------------------------------

Insert Figure 2 about here

------------------------------------

I argue that decision making in the stages of searching, selecting, and implementing will

be very different for managers and entrepreneurs, given the differences between them that have

been documented in the literature. It is highly likely that such differences in decision making

will lead to different performance outcomes. However, the analysis of the performance

outcomes is outside the scope of this article, and I will exclusively focus on the difference

involving decision making.

Managers and entrepreneurs – different decision-making models

Search phase

Timing of awareness of potential ethical issues

From a review of the literature on the RI and effectuation frameworks and from the

general understanding of the different decision-making models pertaining to managers and

entrepreneurs, it can be argued that one of the key factors that differentiates the two kinds of

actors with respect to the RI framework in the search phase is the timing of their awareness

about potential ethical issues in their respective innovation projects. This timing of awareness

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is influenced by the decision-making models that managers and entrepreneurs engage in

respectively. It has been well documented in literature, that managers follow a causal decision-

making path, whereas the route that entrepreneurs follow is influenced more by the logics of

effectuation (Sarasvathy, 2001).

According to Sarasvathy, the causal model begins with a pre-determined goal and a

fixed set of given means. This is true in most organizational context because firms possess

specific sets of resources and capabilities, which give them unique competitive advantages.

However, the resource specificity also limits the extent of exploration of goals and means to a

given limited set. Armed with these limited sets of means, managers seek to identify the optimal

alternative paths to achieve the stated goals.

The effectual decision-making route is different because it does not begin with a set of

given goals. Instead, it begins with a given set of means specific to the entrepreneurs in

question, and the goals emerge contingently over time as a function of the imaginations and

aspirations of the entrepreneurs and their respective networks (Sarasvathy, 2001).

Proposition 1a: Managers, who generally follow a causation driven decision-making pattern,

are likely to have a general idea about the ethical implications of the outcomes of the potential

innovation projects early on during the search phase. This is because in causation processes,

the ultimate goals are given, and the managers scout for means to reach those goals.

Proposition 1b: Entrepreneurs, who generally follow an effectual decision-making pattern, are

likely to become aware of the ethical implications of their decisional much later in the search

phase of innovation projects. This is because in a classical effectual decision-making, the

potential outcomes start taking concrete shape much later in the decision-making process.

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Selection phase

Mode of selection – exploration versus exploitation

Organizational adaptation and adoption are characterized by the perennial tension and

trade-off between exploration and exploitation (March, 1991). In order to ensure a sustainable

and promising future, organizations make uncertain investments and make decisions regarding

resource allocation. These decisions are vital for a firm’s survival while overcoming various

selection pressures in the short-run (Levinthal & March, 1993). The selections are influenced

by a firm’s preference for strategies with respect to exploration and exploitation. The general

conceptualization of exploration, as emphasized by extant literature, makes it look like a

somewhat random and undirected process. However, Adner & Levinthal (2008) suggest that

such a view of exploration is rather biased and misleading. Of course, exploration activities

allow some slack at the policy level. But the slack in question is with regards to the processes

of evaluation of available options and the subsequent selection mechanisms within

organizations (Adner & Levinthal, 2008).

Selection is facilitated within organizations through coordinated actions among groups

of individuals who are often disparate (Adner & Levinthal, 2008). This might potentially lead

to the classical agency problem, arising out of conflict of interests of the different groups in

question. However, the interests are often made to align by reducing divergent behavior

through incentive mechanisms. Another way of doing it is through socialization initiatives and

through the development of shared common identities and shared motives (Adner & Levinthal,

2008). However, organizational managers are subjected to external and internal institutional

pressures (Judge & Zeithaml, 1992) which influence the ethical aspects of their decision

making. Ethics and institutional pressures can influence the exploration / exploitation tradeoff

of organizational managers. Literature has highlighted the role of organizational hierarchy in

ethical decision making.

109

In his study on managers who were lower in the organizational hierarchy, Carroll

(1978) found that those managers felt more pressure to compromise their personal values in

order to achieve company goals. A report on a Wall Street Journal survey (Ricklees, 1983)

revealed that 40 percent of executives stated that they had been asked to behave unethically in

certain stages. Another study posited that middle managers were more ethical than top

management and that the ethical standards of those managers were even higher than those

mandated by existing corporate policies (Ferrell & Weaver, 1978).

I argue that because of the various organizational and institutional forces that managers

are subject to, their decisions regarding selections pertaining to innovation projects will reflect

these forces. Organizations are essentially hierarchical systems, and within the hierarchy, each

manager, because of the aforementioned forces and also because of his/her personal ambition,

is predominantly exploitative. Accordingly, I propose:

Proposition 2a: Organizational managers will engage more in exploitation of existing

resource, capabilities and opportunities while making decisions in the selection phase of

innovation projects. This is predominantly because of the various institutional (external) and

organizational (internal) forces that they are subject to. These forces are more likely to

supersede their personal preference to exploitation / exploration. The ethical dimension of this

mode of decision making is likely to be a function of the ethical stands of their respective

organizations.

It is established by literature that even though there could be a diversity of opinion

within organizations, normally every organization has a dominant political coalition which

decides on various aspects on the organization, including resource allocation for innovation

110

projects. (Prahalad & Bettis, 1986). This might be viewed as a constraint by entrepreneurs, who

typically prefer to have vocational independence from such forces. Often it is difficult for

entrepreneurial individuals to convince the dominant political coalition to pursue opportunities

that they feel to have immense promise. Such individuals are also motivated by the potential

incentives for themselves for pursuing those opportunities (Christensen, 1997; Klepper &

Sleeper, 2005).

Entrepreneurs seek to create and capture value through a combination of exploration

and exploitation of innovation opportunities. They usually do so either by progressing existing

setups and opportunities, or by creating new ones (Blanco 2007). While entrepreneurs are

usually more creative and innovative and are often prone to changing the existing status-quo,

it is practically impossible to create all sets of resources and capabilities towards the pursual of

innovation, from scratch.

Proposition 2b: In the selection phase, entrepreneurs are more likely to engage in both

exploration and exploitation while making decisions. This is predominantly because while

entrepreneurs often create new ways of organizing from existing ones, not everything can be

created from scratch, and entrepreneurs need to utilize existing resources and capabilities in

addition to exploring for something new. The ethical dimension of this mode of decision making

is likely to be a function of the ethical stands of the respective entrepreneurs, as they are

relatively free from the organizational and institutional pressures that managers are subjected

to.

Implementation phase

Risk attitude (risk-averse versus risk-taking)

111

In the variation-selection-retention framework, the last stage is the implementation

phase, where the selected innovation projects are brought to life. The difference between

entrepreneurs and managers with respect to their risk attitudes influences their decision-making

in this phase.

Different kinds of assessments make up key components of the RI framework. One

such assessment is the risk assessment, which is used to connect the RI framework to

innovation (Owen & Goldberg 2010). Risk assessments require a clear picture of the future and

hence, foresight activities are key aspects of the RI framework. Some of the documented ways

of doing such foresight activities are futures studies (Sardar 2010) or foresight research (Cuhls

2003; Martin 2010). Research has established that grand challenges are particularly addressed

thought the practice of foresight activities (Cagnin, Amanatidou, & Keenan 2012), and one of

the grand challenges is the management of the unknown future, which is a key characteristic if

innovation projects.

In his seminal work, Knight (1921) identified three types of uncertainties. The first one,

which is now classified as “risk” talks about a future with a known distribution. Only the

particular raw that will occur is the unknown in this particular scenario. The second one, now

known by the term “uncertainty”, talks about a future whose distribution is unknown. However,

the distribution can be estimated by studying draws over time. The third and the final type was

called “true uncertainty” (or Knightian uncertainty) and consists of a future whose distribution

is unknown and unknowable. This is the kind of future that managers and entrepreneurs face

while managing innovation projects and their decision making is hugely influenced by their

risk attitude.

In large corporations, managers are generally reluctant to propose and undertake risky

projects. As a general trend, it has been observed that such managers are risk averse (Amihud

& Lev, 1981), tend to favor marginal improvements, cost-cutting and safer investments over

112

radical projects (Kahneman & Lovalo, 1993). Kahneman & Tversky (1979) also posited that

decision makers in organizations are more prone to placing greater weights on the economic

losses that could result from their decisions than on potential gains. Why are managers in large,

hierarchical organizations so risk-averse? According to Swalm (1966), in addition to the

control mechanisms that are in place, corporate incentives are designed in a way, that they

active discourage organizational managers from taking risks. Managers in Swalm’s study also

indicated that this kind of defensive risk attitude was good for their carriers, even though they

were bad for the organizations.

Proposition 3a: Managers in organizations are generally risk-averse, and hence will be more

prone to making decisions that are conservative from an ethical perspective. Because of

various institutional and organizational pressures and control systems in place, and because

of their career ambitions, they will be less likely to push the boundaries on ethical grounds

when it comes to decision-making on innovation projects.

Extant literature on entrepreneurs posit that they are risk takers and rugged individualists

(Begley & Boyd 1987; McGrath et al. 1992), and that they engage in deviate social behavior

(Shapero 1975). Entrepreneurs have been observed to accept higher levels of risk in their

careers and also on the domain of business decision-making. (Bird 1989). This is also evident

in the fact that they are involved in starting new ventures, and new ventures usually have higher

probabilities of failure. Busenitz & Barney (1997) found that entrepreneurs are more prone to

using biases and heuristics in strategic decision making and that they are often overconfident

in their decisions. However, the affordable loss principle of effectuation (Sarasvathy, 2001)

posits that entrepreneurial decision-making takes into account the maximum loss that the

113

entrepreneurs are willing to make. I argue that such attitudes in decision-making will have an

impact on the ethical aspects of innovation projects.

Proposition 3b: Entrepreneurs are usually more risk-taking, and overconfident in their

decision making, and hence they are more likely to take non-conservative decisions in the

implementation phase of innovation projects which are likely to push the ethical boundaries to

some extent. The affordable-loss principle of effectuation would suggest that such boundary-

pushing decisions would take into account the maximum loss that entrepreneurs are willing to

make as a consequence.

Conclusion

The synopsis of the current conceptual analysis of the differences between managerial and

entrepreneurial decision-making is represented in Table 1 below.

------------------------------------

Insert Table 1 about here

-------------------------------------

In the next stage of the project, I propose to collect data from the field to validate the

propositions. I am in the process of identifying firms that work in the domain of artificial

intelligence (AI) and I intent to conduct detailed ethnographic study of multiple innovation

projects in those firms. I will study the various antecedents, with a particular emphasis on

decision-making, and their respective roles in selected AI projects that raise ethical questions,

to find out how such questions are handled by managers and entrepreneurs respectively in order

to achieve responsible innovation (RI) outcomes.

114

I will apply the framework of radical and incremental innovations as proposed by

Henderson & Clark (1990) for this study to classify the projects. However, the aforementioned

framework is predominantly applicable for component-based innovations. I might need to

redefine the dimensions of the framework to make it fit in the context of AI, whose nature is

predominantly virtual.

Since the study is in its early stages, and is of a theory-building nature, I will adopt a

qualitative approach as recommended by the literature (e.g. Eisenhardt, 1989). Extant literature

also posits that case studies are justified epistemologically for such projects (Stuart et al., 2002;

Yin, 1989). Furthermore, my decision to study multiple projects in multiple organizations is

influenced by the findings of extant literature that multiple case studies provide a stronger base

for theory building (Rowley, 2002). The data collection methods will predominantly employ

ethnography, where I will shadow AI projects and also conduct semi structured interviews with

the relevant stakeholders of those projects. I will follow the grounded theory approach (Glaser

& Strauss, 1967; Strauss & Corbin, 1997) to analyze the data and to build the model of

governance for RI outcomes. I might also analyze secondary data to triangulate my findings.

Subsequently, I intend to contribute to the literature on RI, ethical governance of innovation

projects, and managerial and entrepreneurial decision-making.

115

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Appendix

Figure 1: Circular process model of RI - taken from Nathan (2015)

Figure 2: Linking stages of Nathan’s model with dimensions of RI

Search Select Implement

Anticipatory Reflective Deliberative

First three stages

in Nathan’s

model

Responsive Corresponding

RI dimensions

Key comparison

dimensions

between

managers and

entrepreneurs

Timing of awareness of

potential ethical issues

Risk attitude

– risk-taker

versus risk-

averse

Mode of

selecting -

exploration

versus

exploitation

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Table 1: Summary of comparison between managerial and entrepreneurial decision-

making in the context of responsible innovation

Stages in Nathan’s

Model (2015)

involving decision

making

Search Select Implement

Dimensions of RI

(Own et al. 2013)

Anticipatory Reflective Deliberative Responsive

Managerial

decision-making

Proposition 1a Proposition 2a Proposition 3a

Entrepreneurial

decision-making

Proposition 1b Proposition 2b Proposition 3b