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RFID Technology in the Indian Retail Sector
There is growing interest and investment in the use of radio frequency identification
(RFID) technology as a means of greater visibility in supply chains, leading to improvedinventory management through improved customer and sales information in retail chains.
Retailing is emerging as a technology-intensive industry, and China and India are
emerging as potential major retail countries. Given the growing importance of the retail business and application of information and communications technologies (ICTs),
particularly RFID, it is important to understand RFID technology per se and its likely
benefits in the retail sector in a developing country like India, where even bar codes arestill not ubiquitous. We discuss RFID technology and its potential scope in the retail
sector briefly, and the Indian retail sector in considerable detail. Thereafter, we discuss
the findings of field case studies of three upcoming retail chains, all of which are workingon identifying the possibility of switching to RFID from bar codes in the coming future.We attempt to understand how RFID application is likely to impact their operations and
supply chains. We develop an adoption and implementation barrier framework and find
out where the three retail chains stand in this framework. Finally, we suggest managerialrecommendations, as well as directions for future work.
Information Technology in Indias real retail sector
October 26, 2007 at 5:06 pm | Posted in Accounting, International business | Leave a
comment
Having been in IT industry and being based in India for a good part of the last decade we
have now got used to relatives and friends with retail outlets small and big asking us
about computers and software and our advise on how to go about them. Most of the
questions relate to accounting perhaps acc101 can be a place where software for
accounting and related items are discussed.
A question that has been generally asked is whether they have to purchase tally, the most
popular accounting package in India or ask their relative or somebody in their
neighborhood who has done a course from NIIT or similar training institutes to help them
create a new software to be used in their shops. We have not had an opportunity to check
which of the two is a better option. Our experience in developing, implementing, selling
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2/42
products and managing software projects and infrastructure for large financial institutions
tell us that a standardized product with solution for all has not been developed yet. And a
pure service based product where you get what you want has its own set of problems
why re-invent the wheel that already exists. The answer is perhaps somewhere in between
and it is too early for us to comment about the proportion in which the two should be. On
an emotional basis, it is a pleasure to ask somebody to develop something for your
business exactly what you want. You will also seed the local IT market. Would you
rather buy a custom made bed or buy a standard and get adjusted to it.
Considering the number of queries that we have got from various quarters like shop
keepers (mainly), textile units small and medium scale and many others in areas
relating to Accounting, Billing, Value Added Tax (VAT), Income tax, Inventory
Management and many others; we came to a conclusion that the real Indian retail sector
has to be investigated. In the meanwhile we though we will put across out experiences to
our folks and other our peers in the industry who face similar questions.
If one has already decided to get that contact of yours to write a new software please keep
in mind a few things you may actually be spending your money on it. We have tried to
list them here randomly.
1. Purpose: Does it serve the purpose that you wish to solve. Just visualize things
like how the solution will look after every thing is done, ask the person to tell you
how it will look, whether you, your assistants, your grand father who will sit at the
cash box and other be able to use it. Can you generate the reports that you want. Are
you complicating your life further and will you have to hire somebody else to work
the software while you sell your goods. You will be surprised how much of problem
it will be for you if you do not know how to click and where to click. If you are not
convinced then do not loose heart, get the correct solution. Ensure that your
8/6/2019 RFID Technology in the Indian Retail Sector
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requirements are met and at the end of the day you should be doing things better and
faster and making more money.
2. Competence: Software may not be rocket science but it is not childs play either.
Does the person developing the application have the necessary competence. As it
takes experience to run a shop like yours it takes a lot of experience to conceptualize
and execute an IT project. This does not mean that you should drop your young
friend from the project. The right way would be to assign a mentor, somebody who
knows. There could be a few who would want to do consultancy for free out of good
will.
3. Organization: I am not speaking about the company here, the person who is
developing the product should have the capability to provide solution in organized
parts. It is like building a great institution, we need not do everything in one go, but
in steps. The organization should be clear. In addition, the trend in technology and
also needs change rapidly. The person developing the application should have the
capability to envisage all these needs or atleast make provisions for them. You dont
want to be stuck with something that is not changeable but your business will.
4. Hardware and other software: Software require a computer to run, you know
this. Your relative may be developing something that will require investment to
work on. Clearly understand your costs for this. What you will require is not just a
computer but many other software that will be required to run on it. These are
typically Operating system like Windows and other things on which the software
will run. These are not free. Taking the discussion further some of these will become
old models so to say. Therefore, your friend should know what is happening in the
market. He may use something cheap but tomorrow it may not be available in the
market, this is more like your spare parts. Your may not get them. As much as
possible get something that is well known.
5. Running Costs: Like your car will require petrol, diesel or otherfuel your
computer and your new software has running costs. One the one hand there are
standards issues but you should also keep in mind that your software also require
repairs and you will require a mechanic for it. This could involve costs.
6. Maintenance: Extending the previous point, once you have installed the software
your friend will have to be the mechanic. He should not run away or get into some
other job. This you should take care.
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7. Electricity: In India, electricity is still an issue. What will you do when there is
no current. Think about it, will you write it in a book and then input it into the
computer. Your friend should answer that question.
8. Backup: Your computer may crash (it does believe me) and what will happen to
your data. Your software should make provision for back up and more importantly
recovery. The data backed up and recovered should not be out of sync. This is a big
subject.
9. Regulations: This relates to government, currently this may not be a big deal in a
software, but it will be in the future.
10. Other applications: You may want to data that is created by your
software to be fed into other software like tally. This should be possible. Design your
requirements appropriately.
11. Language: This is another point that you should consider. For the moment
let us leave it to English. Do you have a key board in your local language.
12. Security: Have a basic security atleast. It is ultimately your data and you
should not let somebody tamper with it. More the security, the better it is.
13. User Manuals: If you have a problem or you dont know how to use it
you will need something to refer to. Get the user manuals preferably in your
language preferably.
14. Data: This is something more into the software. If you can get a data
model.
Competition is increasing at all levels. Biggies are entering small business in the
name of consumption power of the masses. They are well armed. IT is sufficiently
powerful ammunition for smaller players to compete with the big fishes. Perhaps, this
trend will herald a new era of software product and services in India where IT is not
exclusive but instead is a common commodity used by all and sundry whether
custom made or productized.
.
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Factors of new technology adoption in the retail sector.
In recent years, small manufacturing enterprises have been implementing new
computerized technologies at an every-increasing rate (Acs & Audretsch, 1990; Julien,
Estime, & Drilhon, 1993), and the trend is being accelerated by international competition,
in particular by the opening up of national boundaries. However, the same urgency does
not seem to exist in the commercial and service sectors, especially among independent
retailers (Robertson & Gatignon, 1986; Treadgold, 1989; Julien & Thibodeau, 1991).
Certainly, competitive pressure is relatively less intense in these sectors, or at the very
least, certain small businesses have an advantage in terms of location, knowledge of their
clients and their merchandise, or profit from niches created by market segmentation (for
example, gourmet food stores or high fashion boutiques), They are thus under less
pressure to become computerized; they may also be less likely to do so and may not
believe new information technologies to be very useful because, for example in
merchandise analysis, they know their customers and merchandise intimately.
Many small retailers, though, whose ability to differentiate themselves from their
competitors is limited, are feeling increasing competitive pressures, especially with thegrowth of chains and the advent of warehouse stores. A majority of these have neither the
experience nor the financial resources required to plan, implement, and operate a
computer-based information system (Raymond & Lorrain, 1992). But others have begun
to systematically install new point-of-sales (POS) terminals or link up to wholesalers by
tele-computing or electronic data interchange (EDI) (Sweeney, Putnam, Brooks, Hyde,
Lee, Rubel, Rossiter, Armstrong, & Koenigsberg, 1990; Blili & Raymond, 1993).
There may be many reasons for these behavioral differences, even among firms in the
same industry facing the same type of market. In the manufacturing sector, macro-
economic factors such as the rate of economic growth and the competitive structure of the
industry can be determinant (Bouchut, Cochet, & Jacot, 1984; Julien & Thibodeau,
1991). Researchers have also shown that more "technology-consuming" firms are
distinguished from others by: greater profitability, the differential cost of new equipment
(Mansfield, 1971, 1975; Khan & Manopichetwattana, 1989); the management profile or
8/6/2019 RFID Technology in the Indian Retail Sector
6/42
the owner-manager's personal characteristics (Miller & Toulouse, 1986); organizational
complexity, centralization and formalization (Cohn & Turyn, 1980, 1984; Meyer & Goes,
1987; Collins, Hage, & Hull, 1988); strategy type (Garsombke & Garsombke, 1989); and
the quality of technological information obtained together with the capacity to process it
(Blili & Raymond, 1993; Julien, Carriere, & Hebert, 1988; Gatignon & Robertson, 1989).
However, very little research has been done on the reasons for new technology adoption
in the service and retail sectors. To our knowledge, only Treadgold (1989) and Hogarth-
Scott and Parkinson (1990) have examined the question. Treadgold showed that
differences in new technology adoption could be explained by the type of external
organization (for example, between independent businesses and businesses belonging to
groups) and the industry sector. Hogarth-Scott and Parkinson, for their part, showed that
the limited use of EDI technologies among independent businesses stemmed from theirfear of losing their independence. Miller, Glick, Yau-De, & Huber, (1991) have also
indicated that organizations in the retail and service sectors have narrower ranges than in
manufacturing on both technology and structure variables, and thus tend to exhibit
weaker technology-structure relationships
The aim of this research, using empirical evidence, was to identify organizational,
structural, and strategic factors underlying the level of penetration of various
management, service, and information technologies among small retailers, including both
independent businesses and those affiliated to trade banners or buying combines.
Potential factors were identified from the previously cited literature, and in particular
from Julien, Carriere, and Hebert's (1988) study done in the manufacturing sector.
RESEARCH MODEL
The research model is presented in Figure 1. A first set of factors, thought to influence
new technology adoption in small retail firms, describes the structural sophistication of
the firm in terms of centralization and complexity. In the organization theory literature,
structure has often been characterized along these two dimensions or composite factors
(Ford & Slocum, 1977; Miller, 1987). This includes prior research on the technology-
structure relationship (Miller et al., 1991). Decentralizing and complexifying structure
implies more elaborate communication, coordination, and control The aim of this
research, using empirical evidence, was to identify organizational, structural, and
strategic factors underlying the level of penetration of various management, service, and
8/6/2019 RFID Technology in the Indian Retail Sector
7/42
information technologies among small retailers, including both independent businesses
and those affiliated to trade banners or buying combines. Potential factors were identified
from the previously cited literature, and in particular from Julien, Carriere, and Hebert's
(1988) study done in the manufacturing sector.
RESEARCH MODEL
The research model is presented in Figure 1. A first set of factors, thought to influence
new technology adoption in small retail firms, describes the structural sophistication of
the firm in terms of centralization and complexity. In the organization theory literature,
structure has often been characterized along these two dimensions or composite factors
(Ford & Slocum, 1977; Miller, 1987). This includes prior research on the technology-
structure relationship (Miller et al., 1991). Decentralizing and complexifying structure
implies more elaborate communication, coordination, and control Cohn & Turyn, 1984;
Miller & Toulouse, 1986; Raymond, Pare, & Bergeron, 1993).
The second set of adoption factors is strategic in nature, identifying the level of
assertiveness, rationality, and interaction in business decision processes. These three
factors have emerged in the strategy literature as fundamental dimensions or derivative
constructs of the strategy concept (Miller, 1987; Venkatraman, 1989). The first
dimension refers to the proactiveness of decisions and risk taking. The second one
concerns the planning and formulation of strategies. The third one refers to the
political/bargaining processes that bear upon decisions. Information technology has
become one of the key elements in the definition and realization of strategic objectives
(Vitale, Ives, & Beath, 1986). In an increasingly complex environment, organizations
must "align" their use of information technology with the implementation of their
strategic decisions (Chan & Huff, 1993). Thus, when they are more proactive, more
future/planning-oriented, and when more executives interact in strategy making, retailers
would be more apt to implement computer-based information systems resulting from or
in support of their strategy (Shrivastava & Grant, 1985; Schroeder, Gopinath, &
Congden, 1989).
8/6/2019 RFID Technology in the Indian Retail Sector
8/42
The third set of factors thought to influence new technology adoption in small retail firms
are organizational, including size, sector, and status (independent or affiliated).
Organization theorists have found the first two contingency variables to consistently play
an important role in structure-technology-strategy relationships (Ford & Slocum, 1977;
Miller et al., 1991). One expects larger firms to have adopted more sophisticated
technologies (Dewar & Dutton, 1986; Raymond, Pare, & Bergeron, 1993). The same can
be said of firms in more information-intensive retail sectors, e.g. hardware as opposed to
clothing (Kimberly & Evanisko, 1981). Firms who become linked to banners or buying
combines, as opposed to remaining independent, would also be greater users of
information technology (Tornatsky & Klein, 1982). The greater technological
sophistication obtained by retailers who cooperate among themselves would tend to
reduce environmental uncertainty in terms of markets and competitors (Huber, 1984).
The seven factors of new technology adoption were chosen due to their fundamental
nature as descriptors of structure, strategy, and organizational contingencies. These
factors have also been identified as fundamental determinants of technology, both
theoretically and empirically, and all have been used previously in the small business
research context. Note that many of the organization theory and strategic management
studies cited here point to the interdependence of strategy and structure, and to the
contingent role of size and sector in this regard. However, given the focus and objectives
of this study, expected interrelationships between structure, strategy, and organizationalcontingencies were not made explicit in the research model.
No distinction was made between management and production technologies as indicators
of technological levels because in retailing, unlike manufacturing (Raymond & Pare,
1992), it is difficult to differentiate the two. In addition, the actual level of independence
or involvement in a group was not measured, even though some retailing groups (buying
combines, trade banners, coops, franchises) exercise more control over their members
than others. However, franchisees were excluded from the study because, in contrast to
the other groups, their independence is very restricted (Castrogiovanni, Bennett, &
Combs, 1993). In the Canadian province of Quebec, where the survey took place,
independent retailers and members of buying groups or coops are responsible for more
than 72% of all retail sales, at the expense of chains and megastores, whereas in the rest
of Canada and in the U.S.A., their share is much smaller
8/6/2019 RFID Technology in the Indian Retail Sector
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RESEARCH METHODOLOGY
The survey was carried out by collecting data from a sample of small retailers in the food,
hardware, and ladies' garment sectors. Their names were obtained from the central
business data bank of Quebec's commission on health and safety in the workplace(CSST). The survey was performed in two stages. First, 1,200 letters were sent out to the
addresses provided by the CSST, requesting an interview with the owner (4.8% of these
were returned due to improper addresses or out-of-business situations). Among the 232
(19.3%) who were willing to cooperate, a total of 79 retailers were selected for semi-
structured interviews in the field, with the help of a questionnaire. Using CSST data for
the entire 1,200-firm population, the 79 firms were chosen on a stratified sampling basis,
to be statistically representative of this population in terms of size and regional
distribution for each sector. This was verified through chi-square and t tests. Thequestionnaire included 56 closed questions and six open questions, divided into four
sections: the firm's demographics (size, status, etc.), structure, computer hardware and
software, and strategy. A pre-test was done using three firms from each of the three
sectors. Interviewing was deemed preferable to mailing the questionnaire, due to the
technical or open nature of many questions, and to acquire more in-depth information
Two main types of technology were distinguished in the survey: hardware for business
computing (computers), point-of-sales computing (computerized cash registers, whether
or not linked to a central processing unit), and tele-computing (electronic links with
outside firms, usually wholesalers); and software, assessed by the nature of the
applications portfolio. The measures of hardware and software technology adoption, i.e.
the dependent variables, were adapted from previously developed instruments by Julien,
Hebert, and Carriere (1988) and by Raymond and Lorrain (1992). Two main dimensions
of structure--centralization and complexity--were assessed by measuring the managerial
hierarchy (number of managers excluding the owners(s)/all personnel) and the
administrative apparatus (clerical workers/all personnel), both measures previously
validated and used in a small business context (Paulson & Stump, 1979). Complexity was
also ascertained by the presence of a management committee (Julien, Hebert & Carriere,
1988). The same was done with the three principal components of strategy, namely
assertiveness, rationality and interaction. Miller's (1987) instrument was used to measure
strategic orientation (or proactiveness: reactive-proactive) for the first dimension,
8/6/2019 RFID Technology in the Indian Retail Sector
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organizational time-frame (or futurity: short-long term) for the second one, and strategic
decision making (individual-consensual) for the third one.
Table 1 shows the descriptive statistics of the research variables. Thirty-six percent of
firms operated in the food sector (grocery stores, butchers, etc.), 40% in the hardwaresector and 24% in the garment sector. They employed an average of 14.5 people
(excluding owners), including 2.5 office staff. In all, slightly over 50% of the businesses
were affiliated to a trade banner or buying combine, and 46% had a management
committee. Strategically speaking, they were fairly proactive (4.0 on a scale of 1 to 7),
had a medium time-frame (2.7 on a scale of 1 to 5), and shared the decision-making
process to a moderate degree (4.0 on a scale of 1 to 7).
ADOPTION OF NEW TECHNOLOGIES
The overall survey results show that 63 of the 79 firms questioned (79.7%) used at least
one computer-based technology (i.e. electronic cash registers), a higher number
TABULAR DATA OMITTED than the 71% forecasted by Collard (1989) for 1993 in the
United States. The percentage is higher in the food sector (92.8%) than in the hardware
(84.4%) and garment (57.9%) sectors. In all, 36 firms (46.2%) used only stand-alone
electronic cash registers, 11 (14.0%) used cash registers linked to a central register, and
16 (20.5%) had a cash register system linked to a computer. Eight firms (10.0%) had only
a fax or telex, 31 (39.4%) maintained outside links by modem for batch data transfers or
financial transactions (with banks), and 21 (26.9%) maintained systematic outside links
through computers or terminals (EDI).
The number of business computing applications varied from zero to four. Eight firms
(10.1%) indicated using four applications, 16 (20.2%) used three, ten (12.7%) used two,
and four (5.1%) used only one application. In all, 41 firms (51.9%) did not use any form
of business computing. Overall, the type of technology least used by sample firms turned
out to be business computing and related applications. The other two technologies were
more widespread, as only 15 firms (19.0%) did not have an electronic cash register (POS
computing) and 18 (22.8%) did not have an electronic link with an outside organization
(tele-computing). Table 2 summarizes mean adoption rates for each technology (using 5-
point sophistication scales)
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DETERMINANT FACTORS OF NEW TECHNOLOGY ADOPTION
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In recent years, small manufacturing enterprises have been implementing new
computerized technologies at an every-increasing rate (Acs & Audretsch, 1990; Julien,
Estime, & Drilhon, 1993), and the trend is being accelerated by international competition,
in particular by the opening up of national boundaries. However, the same urgency does
not seem to exist in the commercial and service sectors, especially among independent
retailers (Robertson & Gatignon, 1986; Treadgold, 1989; Julien & Thibodeau, 1991).
Certainly, competitive pressure is relatively less intense in these sectors, or at the very
least, certain small businesses have an advantage in terms of location, knowledge of their
clients and their merchandise, or profit from niches created by market segmentation (for
example, gourmet food stores or high fashion boutiques), They are thus under less
pressure to become computerized; they may also be less likely to do so and may not
believe new information technologies to be very useful because, for example inmerchandise analysis, they know their customers and merchandise intimately.
Many small retailers, though, whose ability to differentiate themselves from their
competitors is limited, are feeling increasing competitive pressures, especially with the
growth of chains and the advent of warehouse stores. A majority of these have neither the
experience nor the financial resources required to plan, implement, and operate a
computer-based information system (Raymond & Lorrain, 1992). But others have begun
to systematically install new point-of-sales (POS) terminals or link up to wholesalers by
tele-computing or electronic data interchange (EDI) (Sweeney, Putnam, Brooks, Hyde,
Lee, Rubel, Rossiter, Armstrong, & Koenigsberg, 1990; Blili & Raymond, 1993).
There may be many reasons for these behavioral differences, even among firms in the
same industry facing the same type of market. In the manufacturing sector, macro-
economic factors such as the rate of economic growth and the competitive structure of the
http://www.allbusiness.com/government/government-bodies-offices-us-federal-government/11755722-1.htmlhttp://www.allbusiness.com/company-activities-management/company-structures-ownership/11803672-1.htmlhttp://www.allbusiness.com/company-activities-management/product-management/14814364-1.htmlhttp://www.allbusiness.com/government/government-bodies-offices-us-federal-government/11755722-1.htmlhttp://www.allbusiness.com/company-activities-management/company-structures-ownership/11803672-1.htmlhttp://www.allbusiness.com/company-activities-management/product-management/14814364-1.html8/6/2019 RFID Technology in the Indian Retail Sector
12/42
industry can be determinant (Bouchut, Cochet, & Jacot, 1984; Julien & Thibodeau,
1991). Researchers have also shown that more "technology-consuming" firms are
distinguished from others by: greater profitability, the differential cost of new equipment
(Mansfield, 1971, 1975; Khan & Manopichetwattana, 1989); the management profile or
the owner-manager's personal characteristics (Miller & Toulouse, 1986); organizational
complexity, centralization and formalization (Cohn & Turyn, 1980, 1984; Meyer & Goes,
1987; Collins, Hage, & Hull, 1988); strategy type (Garsombke & Garsombke, 1989); and
the quality of technological information obtained together with the capacity to process it
(Blili & Raymond, 1993; Julien, Carriere, & Hebert, 1988; Gatignon & Robertson, 1989).
However, very little research has been done on the reasons for new technology adoption
in the service and retail sectors. To our knowledge, only Treadgold (1989) and Hogarth-
Scott and Parkinson (1990) have examined the question. Treadgold showed thatdifferences in new technology adoption could be explained by the type of external
organization (for example, between independent businesses and businesses belonging to
groups) and the industry sector. Hogarth-Scott and Parkinson, for their part, showed that
the limited use of EDI technologies among independent businesses stemmed from their
fear of losing their independence. Miller, Glick, Yau-De, & Huber, (1991) have also
indicated that organizations in the retail and service sectors have narrower ranges than in
manufacturing on both technology and structure variables, and thus tend to exhibit
weaker technology-structure relationships.
The aim of this research, using empirical evidence, was to identify organizational,
structural, and strategic factors underlying the level of penetration of various
management, service, and information technologies among small retailers, including both
independent businesses and those affiliated to trade banners or buying combines.
Potential factors were identified from the previously cited literature, and in particular
from Julien, Carriere, and Hebert's (1988) study done in the manufacturing sector.
RESEARCH MODEL
The research model is presented in Figure 1. A first set of factors, thought to influence
new technology adoption in small retail firms, describes the structural sophistication of
the firm in terms of centralization and complexity. In the organization theory literature,
structure has often been characterized along these two dimensions or composite factors
(Ford & Slocum, 1977; Miller, 1987). This includes prior research on the technology-
8/6/2019 RFID Technology in the Indian Retail Sector
13/42
structure relationship (Miller et al., 1991). Decentralizing and complexifying structure
implies more elaborate communication, coordination, and control mechanisms; this in
turn requires an infrastructure that can be better enabled through information technology
(Huber, 1984; Leifer, 1988). Hence, more decentralized management and complex
administrative structures should lead to greater adoption of information technologies by
retailers (Cohn & Turyn, 1984; Miller & Toulouse, 1986; Raymond, Pare, & Bergeron,
1993).
The second set of adoption factors is strategic in nature, identifying the level of
assertiveness, rationality, and interaction in business decision processes. These three
factors have emerged in the strategy literature as fundamental dimensions or derivative
constructs of the strategy concept (Miller, 1987; Venkatraman, 1989). The first
dimension refers to the proactiveness of decisions and risk taking. The second oneconcerns the planning and formulation of strategies. The third one refers to the
political/bargaining processes that bear upon decisions. Information technology has
become one of the key elements in the definition and realization of strategic objectives
(Vitale, Ives, & Beath, 1986). In an increasingly complex environment, organizations
must "align" their use of information technology with the implementation of their
strategic decisions (Chan & Huff, 1993). Thus, when they are more proactive, more
future/planning-oriented, and when more executives interact in strategy making, retailers
would be more apt to implement computer-based information systems resulting from orin support of their strategy (Shrivastava & Grant, 1985; Schroeder, Gopinath, &
Congden, 1989).
The third set of factors thought to influence new technology adoption in small retail firms
are organizational, including size, sector, and status (independent or affiliated).
Organization theorists have found the first two contingency variables to consistently play
an important role in structure-technology-strategy relationships (Ford & Slocum, 1977;
Miller et al., 1991). One expects larger firms to have adopted more sophisticated
technologies (Dewar & Dutton, 1986; Raymond, Pare, & Bergeron, 1993). The same can
be said of firms in more information-intensive retail sectors, e.g. hardware as opposed to
clothing (Kimberly & Evanisko, 1981). Firms who become linked to banners or buying
combines, as opposed to remaining independent, would also be greater users of
information technology (Tornatsky & Klein, 1982). The greater technological
8/6/2019 RFID Technology in the Indian Retail Sector
14/42
sophistication obtained by retailers who cooperate among themselves would tend to
reduce environmental uncertainty in terms of markets and competitors (Huber, 1984).
The seven factors of new technology adoption were chosen due to their fundamental
nature as descriptors of structure, strategy, and organizational contingencies. Thesefactors have also been identified as fundamental determinants of technology, both
theoretically and empirically, and all have been used previously in the small business
research context. Note that many of the organization theory and strategic management
studies cited here point to the interdependence of strategy and structure, and to the
contingent role of size and sector in this regard. However, given the focus and objectives
of this study, expected interrelationships between structure, strategy, and organizational
contingencies were not made explicit in the research model.
No distinction was made between management and production technologies as indicators
of technological levels because in retailing, unlike manufacturing (Raymond & Pare,
1992), it is difficult to differentiate the two. In addition, the actual level of independence
or involvement in a group was not measured, even though some retailing groups (buying
combines, trade banners, coops, franchises) exercise more control over their members
than others. However, franchisees were excluded from the study because, in contrast to
the other groups, their independence is very restricted (Castrogiovanni, Bennett, &
Combs, 1993). In the Canadian province of Quebec, where the survey took place,
independent retailers and members of buying groups or coops are responsible for more
than 72% of all retail sales, at the expense of chains and megastores, whereas in the rest
of Canada and in the U.S.A., their share is much smaller.
RESEARCH METHODOLOGY
The survey was carried out by collecting data from a sample of small retailers in the food,
hardware, and ladies' garment sectors. Their names were obtained from the central
business data bank of Quebec's commission on health and safety in the workplace
(CSST). The survey was performed in two stages. First, 1,200 letters were sent out to the
addresses provided by the CSST, requesting an interview with the owner (4.8% of these
were returned due to improper addresses or out-of-business situations). Among the 232
(19.3%) who were willing to cooperate, a total of 79 retailers were selected for semi-
structured interviews in the field, with the help of a questionnaire. Using CSST data for
the entire 1,200-firm population, the 79 firms were chosen on a stratified sampling basis,
8/6/2019 RFID Technology in the Indian Retail Sector
15/42
to be statistically representative of this population in terms of size and regional
distribution for each sector. This was verified through chi-square and t tests. The
questionnaire included 56 closed questions and six open questions, divided into four
sections: the firm's demographics (size, status, etc.), structure, computer hardware and
software, and strategy. A pre-test was done using three firms from each of the three
sectors. Interviewing was deemed preferable to mailing the questionnaire, due to the
technical or open nature of many questions, and to acquire more in-depth information.
Two main types of technology were distinguished in the survey: hardware for business
computing (computers), point-of-sales computing (computerized cash registers, whether
or not linked to a central processing unit), and tele-computing (electronic links with
outside firms, usually wholesalers); and software, assessed by the nature of the
applications portfolio. The measures of hardware and software technology adoption, i.e.the dependent variables, were adapted from previously developed instruments by Julien,
Hebert, and Carriere (1988) and by Raymond and Lorrain (1992). Two main dimensions
of structure--centralization and complexity--were assessed by measuring the managerial
hierarchy (number of managers excluding the owners(s)/all personnel) and the
administrative apparatus (clerical workers/all personnel), both measures previously
validated and used in a small business context (Paulson & Stump, 1979). Complexity was
also ascertained by the presence of a management committee (Julien, Hebert & Carriere,
1988). The same was done with the three principal components of strategy, namelyassertiveness, rationality and interaction. Miller's (1987) instrument was used to measure
strategic orientation (or proactiveness: reactive-proactive) for the first dimension,
organizational time-frame (or futurity: short-long term) for the second one, and strategic
decision making (individual-consensual) for the third one.
Table 1 shows the descriptive statistics of the research variables. Thirty-six percent of
firms operated in the food sector (grocery stores, butchers, etc.), 40% in the hardware
sector and 24% in the garment sector. They employed an average of 14.5 people
(excluding owners), including 2.5 office staff. In all, slightly over 50% of the businesses
were affiliated to a trade banner or buying combine, and 46% had a management
committee. Strategically speaking, they were fairly proactive (4.0 on a scale of 1 to 7),
had a medium time-frame (2.7 on a scale of 1 to 5), and shared the decision-making
process to a moderate degree (4.0 on a scale of 1 to 7).
8/6/2019 RFID Technology in the Indian Retail Sector
16/42
ADOPTION OF NEW TECHNOLOGIES
The overall survey results show that 63 of the 79 firms questioned (79.7%) used at least
one computer-based technology (i.e. electronic cash registers), a higher number
TABULAR DATA OMITTED than the 71% forecasted by Collard (1989) for 1993 in theUnited States. The percentage is higher in the food sector (92.8%) than in the hardware
(84.4%) and garment (57.9%) sectors. In all, 36 firms (46.2%) used only stand-alone
electronic cash registers, 11 (14.0%) used cash registers linked to a central register, and
16 (20.5%) had a cash register system linked to a computer. Eight firms (10.0%) had only
a fax or telex, 31 (39.4%) maintained outside links by modem for batch data transfers or
financial transactions (with banks), and 21 (26.9%) maintained systematic outside links
through computers or terminals (EDI).
The number of business computing applications varied from zero to four. Eight firms
(10.1%) indicated using four applications, 16 (20.2%) used three, ten (12.7%) used two,
and four (5.1%) used only one application. In all, 41 firms (51.9%) did not use any form
of business computing. Overall, the type of technology least used by sample firms turned
out to be business computing and related applications. The other two technologies were
more widespread, as only 15 firms (19.0%) did not have an electronic cash register (POS
computing) and 18 (22.8%) did not have an electronic link with an outside organization
(tele-computing). Table 2 summarizes mean adoption rates for each technology (using 5-
point sophistication scales).
DETERMINANT FACTORS OF NEW TECHNOLOGY ADOPTION
Shown in Table 3 is the intercorrelation matrix of the independent variables. Given its
highly significant relationship with five other factors, size was removed from further data
analysis to reduce problems due to multicollinearity (Huang, 1970). The same was done
with the decision-making variable, as it is strongly correlated with the other two strategy
variables. Note that after removal of these two variables, two intercorrelations
TABULAR DATA OMITTED greater than 0.3 remain, that is, firms in the clothing
sector and firms with a larger bureaucracy (administrative apparatus) are less likely to
have an affiliated status (r = -0.52, r = -0.35).
As hypothesized, differences in levels of hardware and software technology adoption by
retailers are due to a number of organizational, structural, and strategic factors.
8/6/2019 RFID Technology in the Indian Retail Sector
17/42
TABULAR DATA OMITTED
Shown in Table 4 are the results of stepwise regression analyses on the four technology
variables, revealing the determinant factors in each case. Retailers who adopt business
computing are less likely to be in the food sector and tend to be affiliated to a buyingcombine or trade banner. They are more decentralized, i.e. show a higher ratio of
managers (managerial hierarchy), and are more likely to have a management committee.
Strategic factors do not seem to come into play here.
The adoption of POS computing is determined by a different set of factors. Clothing
merchants are less apt to employ this technology, as are firms with a larger ratio of
clerical personnel (administrative apparatus). In addition, firms with POS technology
have a longer organization time-frame. The use of tele-computing is mostly determined
by the retailer's status as member of a combine or banner, as expected. Firms who have
implemented EDI are also more future-oriented than others, confirming Blili and
Raymond's (1993) conjecture.
Not surprisingly, hardware stores, with their greater information needs (e.g. for inventory
management), are the ones with the more extensive applications portfolio (software),
while more decentralized firms implement a more sophisticated management information
system. These results are in line with the technology-structure relationships found by
Raymond, Pare, and Bergeron (1993). Also, more proactive and future-oriented retailfirms implement a more extensive applications portfolio. This confirms the mutually
determining impact of strategy and information systems in the context of SMEs (Blili &
Raymond, 1993).
Table 4
Regression Analyses on the Four Technology Variables
Standardized betas(a)
Related Articles
Let Small Businesses Lead the Telecom Revolution
Companies Lighting Candles in the Economic Darkness
How the Digital Revolution (and Uncle Sam) Can Revive the Economy
8/6/2019 RFID Technology in the Indian Retail Sector
18/42
In recent years, small manufacturing enterprises have been implementing new
computerized technologies at an every-increasing rate (Acs & Audretsch, 1990; Julien,
Estime, & Drilhon, 1993), and the trend is being accelerated by international competition,
in particular by the opening up of national boundaries. However, the same urgency does
not seem to exist in the commercial and service sectors, especially among independent
retailers (Robertson & Gatignon, 1986; Treadgold, 1989; Julien & Thibodeau, 1991).
Certainly, competitive pressure is relatively less intense in these sectors, or at the very
least, certain small businesses have an advantage in terms of location, knowledge of their
clients and their merchandise, or profit from niches created by market segmentation (for
example, gourmet food stores or high fashion boutiques), They are thus under less
pressure to become computerized; they may also be less likely to do so and may not
believe new information technologies to be very useful because, for example in
merchandise analysis, they know their customers and merchandise intimately.
Many small retailers, though, whose ability to differentiate themselves from their
competitors is limited, are feeling increasing competitive pressures, especially with the
growth of chains and the advent of warehouse stores. A majority of these have neither the
experience nor the financial resources required to plan, implement, and operate a
computer-based information system (Raymond & Lorrain, 1992). But others have begun
to systematically install new point-of-sales (POS) terminals or link up to wholesalers by
tele-computing or electronic data interchange (EDI) (Sweeney, Putnam, Brooks, Hyde,
Lee, Rubel, Rossiter, Armstrong, & Koenigsberg, 1990; Blili & Raymond, 1993).
There may be many reasons for these behavioral differences, even among firms in the
same industry facing the same type of market. In the manufacturing sector, macro-
economic factors such as the rate of economic growth and the competitive structure of the
industry can be determinant (Bouchut, Cochet, & Jacot, 1984; Julien & Thibodeau,
1991). Researchers have also shown that more "technology-consuming" firms are
distinguished from others by: greater profitability, the differential cost of new equipment
(Mansfield, 1971, 1975; Khan & Manopichetwattana, 1989); the management profile or
the owner-manager's personal characteristics (Miller & Toulouse, 1986); organizational
complexity, centralization and formalization (Cohn & Turyn, 1980, 1984; Meyer & Goes,
8/6/2019 RFID Technology in the Indian Retail Sector
19/42
1987; Collins, Hage, & Hull, 1988); strategy type (Garsombke & Garsombke, 1989); and
the quality of technological information obtained together with the capacity to process it
(Blili & Raymond, 1993; Julien, Carriere, & Hebert, 1988; Gatignon & Robertson, 1989).
However, very little research has been done on the reasons for new technology adoption
in the service and retail sectors. To our knowledge, only Treadgold (1989) and Hogarth-
Scott and Parkinson (1990) have examined the question. Treadgold showed that
differences in new technology adoption could be explained by the type of external
organization (for example, between independent businesses and businesses belonging to
groups) and the industry sector. Hogarth-Scott and Parkinson, for their part, showed that
the limited use of EDI technologies among independent businesses stemmed from their
fear of losing their independence. Miller, Glick, Yau-De, & Huber, (1991) have also
indicated that organizations in the retail and service sectors have narrower ranges than in
manufacturing on both technology and structure variables, and thus tend to exhibit
weaker technology-structure relationships.
The aim of this research, using empirical evidence, was to identify organizational,
structural, and strategic factors underlying the level of penetration of various
management, service, and information technologies among small retailers, including both
independent businesses and those affiliated to trade banners or buying combines.
Potential factors were identified from the previously cited literature, and in particular
from Julien, Carriere, and Hebert's (1988) study done in the manufacturing sector.
RESEARCH MODEL
The research model is presented in Figure 1. A first set of factors, thought to influence
new technology adoption in small retail firms, describes the structural sophistication of
the firm in terms of centralization and complexity. In the organization theory literature,
structure has often been characterized along these two dimensions or composite factors
(Ford & Slocum, 1977; Miller, 1987). This includes prior research on the technology-
8/6/2019 RFID Technology in the Indian Retail Sector
20/42
structure relationship (Miller et al., 1991). Decentralizing and complexifying structure
implies more elaborate communication, coordination, and control mechanisms; this in
turn requires an infrastructure that can be better enabled through information technology
(Huber, 1984; Leifer, 1988). Hence, more decentralized management and complex
administrative structures should lead to greater adoption of information technologies by
retailers (Cohn & Turyn, 1984; Miller & Toulouse, 1986; Raymond, Pare, & Bergeron,
1993).
The second set of adoption factors is strategic in nature, identifying the level of
assertiveness, rationality, and interaction in business decision processes. These three
factors have emerged in the strategy literature as fundamental dimensions or derivative
constructs of the strategy concept (Miller, 1987; Venkatraman, 1989). The first
dimension refers to the proactiveness of decisions and risk taking. The second one
concerns the planning and formulation of strategies. The third one refers to the
political/bargaining processes that bear upon decisions. Information technology has
become one of the key elements in the definition and realization of strategic objectives
(Vitale, Ives, & Beath, 1986). In an increasingly complex environment, organizations
must "align" their use of information technology with the implementation of their
strategic decisions (Chan & Huff, 1993). Thus, when they are more proactive, more
future/planning-oriented, and when more executives interact in strategy making, retailers
would be more apt to implement computer-based information systems resulting from or
in support of their strategy (Shrivastava & Grant, 1985; Schroeder, Gopinath, &
Congden, 1989).
The third set of factors thought to influence new technology adoption in small retail firms
are organizational, including size, sector, and status (independent or affiliated).
Organization theorists have found the first two contingency variables to consistently play
an important role in structure-technology-strategy relationships (Ford & Slocum, 1977;
Miller et al., 1991). One expects larger firms to have adopted more sophisticated
technologies (Dewar & Dutton, 1986; Raymond, Pare, & Bergeron, 1993). The same can
be said of firms in more information-intensive retail sectors, e.g. hardware as opposed to
clothing (Kimberly & Evanisko, 1981). Firms who become linked to banners or buying
8/6/2019 RFID Technology in the Indian Retail Sector
21/42
combines, as opposed to remaining independent, would also be greater users of
information technology (Tornatsky & Klein, 1982). The greater technological
sophistication obtained by retailers who cooperate among themselves would tend to
reduce environmental uncertainty in terms of markets and competitors (Huber, 1984).
The seven factors of new technology adoption were chosen due to their fundamental
nature as descriptors of structure, strategy, and organizational contingencies. These
factors have also been identified as fundamental determinants of technology, both
theoretically and empirically, and all have been used previously in the small business
research context. Note that many of the organization theory and strategic management
studies cited here point to the interdependence of strategy and structure, and to the
contingent role of size and sector in this regard. However, given the focus and objectives
of this study, expected interrelationships between structure, strategy, and organizational
contingencies were not made explicit in the research model.
No distinction was made between management and production technologies as indicators
of technological levels because in retailing, unlike manufacturing (Raymond & Pare,
1992), it is difficult to differentiate the two. In addition, the actual level of independence
or involvement in a group was not measured, even though some retailing groups (buying
combines, trade banners, coops, franchises) exercise more control over their members
than others. However, franchisees were excluded from the study because, in contrast to
the other groups, their independence is very restricted (Castrogiovanni, Bennett, &
Combs, 1993). In the Canadian province of Quebec, where the survey took place,
independent retailers and members of buying groups or coops are responsible for more
than 72% of all retail sales, at the expense of chains and megastores, whereas in the rest
of Canada and in the U.S.A., their share is much smaller.
RESEARCH METHODOLOGY
8/6/2019 RFID Technology in the Indian Retail Sector
22/42
The survey was carried out by collecting data from a sample of small retailers in the food,
hardware, and ladies' garment sectors. Their names were obtained from the central
business data bank of Quebec's commission on health and safety in the workplace
(CSST). The survey was performed in two stages. First, 1,200 letters were sent out to the
addresses provided by the CSST, requesting an interview with the owner (4.8% of these
were returned due to improper addresses or out-of-business situations). Among the 232
(19.3%) who were willing to cooperate, a total of 79 retailers were selected for semi-
structured interviews in the field, with the help of a questionnaire. Using CSST data for
the entire 1,200-firm population, the 79 firms were chosen on a stratified sampling basis,
to be statistically representative of this population in terms of size and regional
distribution for each sector. This was verified through chi-square and t tests. The
questionnaire included 56 closed questions and six open questions, divided into four
sections: the firm's demographics (size, status, etc.), structure, computer hardware and
software, and strategy. A pre-test was done using three firms from each of the three
sectors. Interviewing was deemed preferable to mailing the questionnaire, due to the
technical or open nature of many questions, and to acquire more in-depth information.
Two main types of technology were distinguished in the survey: hardware for business
computing (computers), point-of-sales computing (computerized cash registers, whether
or not linked to a central processing unit), and tele-computing (electronic links with
outside firms, usually wholesalers); and software, assessed by the nature of the
applications portfolio. The measures of hardware and software technology adoption, i.e.
the dependent variables, were adapted from previously developed instruments by Julien,
Hebert, and Carriere (1988) and by Raymond and Lorrain (1992). Two main dimensions
of structure--centralization and complexity--were assessed by measuring the managerial
hierarchy (number of managers excluding the owners(s)/all personnel) and the
administrative apparatus (clerical workers/all personnel), both measures previously
validated and used in a small business context (Paulson & Stump, 1979). Complexity was
also ascertained by the presence of a management committee (Julien, Hebert & Carriere,
1988). The same was done with the three principal components of strategy, namely
assertiveness, rationality and interaction. Miller's (1987) instrument was used to measure
strategic orientation (or proactiveness: reactive-proactive) for the first dimension,
8/6/2019 RFID Technology in the Indian Retail Sector
23/42
organizational time-frame (or futurity: short-long term) for the second one, and strategic
decision making (individual-consensual) for the third one.
Table 1 shows the descriptive statistics of the research variables. Thirty-six percent of
firms operated in the food sector (grocery stores, butchers, etc.), 40% in the hardware
sector and 24% in the garment sector. They employed an average of 14.5 people
(excluding owners), including 2.5 office staff. In all, slightly over 50% of the businesses
were affiliated to a trade banner or buying combine, and 46% had a management
committee. Strategically speaking, they were fairly proactive (4.0 on a scale of 1 to 7),
had a medium time-frame (2.7 on a scale of 1 to 5), and shared the decision-making
process to a moderate degree (4.0 on a scale of 1 to 7).
ADOPTION OF NEW TECHNOLOGIES
The overall survey results show that 63 of the 79 firms questioned (79.7%) used at least
one computer-based technology (i.e. electronic cash registers), a higher number
TABULAR DATA OMITTED than the 71% forecasted by Collard (1989) for 1993 in the
United States. The percentage is higher in the food sector (92.8%) than in the hardware(84.4%) and garment (57.9%) sectors. In all, 36 firms (46.2%) used only stand-alone
electronic cash registers, 11 (14.0%) used cash registers linked to a central register, and
16 (20.5%) had a cash register system linked to a computer. Eight firms (10.0%) had only
a fax or telex, 31 (39.4%) maintained outside links by modem for batch data transfers or
financial transactions (with banks), and 21 (26.9%) maintained systematic outside links
through computers or terminals (EDI).
The number of business computing applications varied from zero to four. Eight firms
(10.1%) indicated using four applications, 16 (20.2%) used three, ten (12.7%) used two,
and four (5.1%) used only one application. In all, 41 firms (51.9%) did not use any form
of business computing. Overall, the type of technology least used by sample firms turned
out to be business computing and related applications. The other two technologies were
8/6/2019 RFID Technology in the Indian Retail Sector
24/42
more widespread, as only 15 firms (19.0%) did not have an electronic cash register (POS
computing) and 18 (22.8%) did not have an electronic link with an outside organization
(tele-computing). Table 2 summarizes mean adoption rates for each technology (using 5-
point sophistication scales).
DETERMINANT FACTORS OF NEW TECHNOLOGY ADOPTION
Shown in Table 3 is the intercorrelation matrix of the independent variables. Given its
highly significant relationship with five other factors, size was removed from further data
analysis to reduce problems due to multicollinearity (Huang, 1970). The same was done
with the decision-making variable, as it is strongly correlated with the other two strategy
variables. Note that after removal of these two variables, two intercorrelations
TABULAR DATA OMITTED greater than 0.3 remain, that is, firms in the clothing
sector and firms with a larger bureaucracy (administrative apparatus) are less likely to
have an affiliated status (r = -0.52, r = -0.35).
As hypothesized, differences in levels of hardware and software technology adoption by
retailers are due to a number of organizational, structural, and strategic factors.
TABULAR DATA OMITTED
Shown in Table 4 are the results of stepwise regression analyses on the four technology
variables, revealing the determinant factors in each case. Retailers who adopt business
computing are less likely to be in the food sector and tend to be affiliated to a buying
combine or trade banner. They are more decentralized, i.e. show a higher ratio of
managers (managerial hierarchy), and are more likely to have a management committee.
Strategic factors do not seem to come into play here.
8/6/2019 RFID Technology in the Indian Retail Sector
25/42
The adoption of POS computing is determined by a different set of factors. Clothing
merchants are less apt to employ this technology, as are firms with a larger ratio of
clerical personnel (administrative apparatus). In addition, firms with POS technology
have a longer organization time-frame. The use of tele-computing is mostly determined
by the retailer's status as member of a combine or banner, as expected. Firms who have
implemented EDI are also more future-oriented than others, confirming Blili and
Raymond's (1993) conjecture.
Not surprisingly, hardware stores, with their greater information needs (e.g. for inventory
management), are the ones with the more extensive applications portfolio (software),
while more decentralized firms implement a more sophisticated management information
system. These results are in line with the technology-structure relationships found by
Raymond, Pare, and Bergeron (1993). Also, more proactive and future-oriented retail
firms implement a more extensive applications portfolio. This confirms the mutually
determining impact of strategy and information systems in the context of SMEs (Blili &
Raymond, 1993).
Table 4
Regression Analyses on the Four Technology Variables
Standardized betas(a)
HARDWARE SOFTWARE
ENTERPRISE TYPOLOGY AND NEW TECHNOLOGY ADOPTION
To typify the sampled firms in terms of overall technology adoption, a hierarchical
cluster analysis on the four technology (dependent) variables was used to divide the
sampled firms into three groups: 45 firms using very few or no hardware and software
technologies (type 1: LOW TECHNOLOGY); 18 favoring technology for administrative
8/6/2019 RFID Technology in the Indian Retail Sector
26/42
and managerial purposes (type 2: MANAGEMENT TECHNOLOGY); and 16 using
technologies to enhance organizational value and performance (type 3: VALUE
TECHNOLOGY). Business computing is used equally by the firms in types 2 and 3;
these two groups also exhibit the same level of sophistication in their applications
portfolio. However, POS and tele-computing are used significantly more by type 3 than
type 2 retailers. Type 1 firms use some POS and tele-computing but almost no business
computing or applications.
Table 5 presents a breakdown of the adoption factors (independent variables) for the
TABULAR DATA OMITTED three types. Type 3 merchants (those seeking value) have
the greater size, operate more in the hardware sector, and are generally affiliated.
Management is often the responsibility of more than one person, but is less bureaucratic
than in the other two types. More than two-thirds of businesses in type 3 have amanagement committee, and most tend to have more proactive and long-term strategies.
The strategic decision-making process is usually shared.
Type 2 firms (those favoring technological management) are evenly spread over the three
retail sectors, but are more bureaucratic than type 3 firms. Their strategies are as
proactive and the decision-making process is shared to a similar degree, but their time-
frame tends to be shorter. Type 1 businesses (those making little or no use of
technologies) have the fewest employees and are least likely to be affiliated to trade
banners or buying combines. They operate mainly in the food sector. Management is
generally the responsibility of one person, but these organizations are more bureaucratic
than the other two types, and little use is made of management committees. They tend to
be reactive, have a shorter time-frame, and the decision-making process is rarely shared.
Overall, the more value- or performance-oriented the business, the more it will adopt
many different technologies. In contrast, small retailers favoring technological
management will favor business computing and implement a larger number of
applications. The remaining majority (type 1) will opt mainly for POS and tele-computing (EDI).
discriminant analysis was performed to establish the importance of each factor in
determining a firm's being categorized as one of the three types. The results are presented
in Table 6. The first variable to enter is the firm's managerial hierarchy (decentralization),
followed by the firm's being in a less information-intensive sector (clothing or food).
8/6/2019 RFID Technology in the Indian Retail Sector
27/42
Differences between types 1, 2, and 3 can also be explained by the firm's status, by the
presence or not of a management committee, and by the administrative apparatus
(structural complexity). The retailer's strategic orientation and time-frame are the last
factors to enter in the analysis. These results are in line with the preceding ones and
confirm the overall validity of the research model as eight variables display significant
explanatory power.
Table 6
Discriminant Analysis of the Three Types of Firms
Type 1: LOW TECH. Type 2: MANAGEMENT TECH. Type 3: VALUE
TECH.
Variable F to Wilks' Min. D.f.
Step entered enter lambda p D(a) coef.(b)
1 Man. hierarchy 6.0 .856 .004 0.2 .442
2 Clothing (sector) 3.4 .781 .002 0.8 -.397
3 Food (sector) 2.5 .728 .001 1.0 -.542
4 Status 3.8
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In recent years, small manufacturing enterprises have been implementing new
computerized technologies at an every-increasing rate (Acs & Audretsch, 1990; Julien,
Estime, & Drilhon, 1993), and the trend is being accelerated by international competition,
http://www.allbusiness.com/government/government-bodies-offices-us-federal-government/11755722-1.htmlhttp://www.allbusiness.com/company-activities-management/company-structures-ownership/11803672-1.htmlhttp://www.allbusiness.com/company-activities-management/product-management/14814364-1.htmlhttp://www.allbusiness.com/government/government-bodies-offices-us-federal-government/11755722-1.htmlhttp://www.allbusiness.com/company-activities-management/company-structures-ownership/11803672-1.htmlhttp://www.allbusiness.com/company-activities-management/product-management/14814364-1.html8/6/2019 RFID Technology in the Indian Retail Sector
28/42
in particular by the opening up of national boundaries. However, the same urgency does
not seem to exist in the commercial and service sectors, especially among independent
retailers (Robertson & Gatignon, 1986; Treadgold, 1989; Julien & Thibodeau, 1991).
Certainly, competitive pressure is relatively less intense in these sectors, or at the very
least, certain small businesses have an advantage in terms of location, knowledge of their
clients and their merchandise, or profit from niches created by market segmentation (for
example, gourmet food stores or high fashion boutiques), They are thus under less
pressure to become computerized; they may also be less likely to do so and may not
believe new information technologies to be very useful because, for example in
merchandise analysis, they know their customers and merchandise intimately.
Many small retailers, though, whose ability to differentiate themselves from their
competitors is limited, are feeling increasing competitive pressures, especially with thegrowth of chains and the advent of warehouse stores. A majority of these have neither the
experience nor the financial resources required to plan, implement, and operate a
computer-based information system (Raymond & Lorrain, 1992). But others have begun
to systematically install new point-of-sales (POS) terminals or link up to wholesalers by
tele-computing or electronic data interchange (EDI) (Sweeney, Putnam, Brooks, Hyde,
Lee, Rubel, Rossiter, Armstrong, & Koenigsberg, 1990; Blili & Raymond, 1993).
There may be many reasons for these behavioral differences, even among firms in the
same industry facing the same type of market. In the manufacturing sector, macro-
economic factors such as the rate of economic growth and the competitive structure of the
industry can be determinant (Bouchut, Cochet, & Jacot, 1984; Julien & Thibodeau,
1991). Researchers have also shown that more "technology-consuming" firms are
distinguished from others by: greater profitability, the differential cost of new equipment
(Mansfield, 1971, 1975; Khan & Manopichetwattana, 1989); the management profile or
the owner-manager's personal characteristics (Miller & Toulouse, 1986); organizational
complexity, centralization and formalization (Cohn & Turyn, 1980, 1984; Meyer & Goes,
1987; Collins, Hage, & Hull, 1988); strategy type (Garsombke & Garsombke, 1989); and
the quality of technological information obtained together with the capacity to process it
(Blili & Raymond, 1993; Julien, Carriere, & Hebert, 1988; Gatignon & Robertson, 1989).
However, very little research has been done on the reasons for new technology adoption
in the service and retail sectors. To our knowledge, only Treadgold (1989) and Hogarth-
8/6/2019 RFID Technology in the Indian Retail Sector
29/42
Scott and Parkinson (1990) have examined the question. Treadgold showed that
differences in new technology adoption could be explained by the type of external
organization (for example, between independent businesses and businesses belonging to
groups) and the industry sector. Hogarth-Scott and Parkinson, for their part, showed that
the limited use of EDI technologies among independent businesses stemmed from their
fear of losing their independence. Miller, Glick, Yau-De, & Huber, (1991) have also
indicated that organizations in the retail and service sectors have narrower ranges than in
manufacturing on both technology and structure variables, and thus tend to exhibit
weaker technology-structure relationships.
The aim of this research, using empirical evidence, was to identify organizational,
structural, and strategic factors underlying the level of penetration of various
management, service, and information technologies among small retailers, including bothindependent businesses and those affiliated to trade banners or buying combines.
Potential factors were identified from the previously cited literature, and in particular
from Julien, Carriere, and Hebert's (1988) study done in the manufacturing sector.
RESEARCH MODEL
The research model is presented in Figure 1. A first set of factors, thought to influence
new technology adoption in small retail firms, describes the structural sophistication of
the firm in terms of centralization and complexity. In the organization theory literature,structure has often been characterized along these two dimensions or composite factors
(Ford & Slocum, 1977; Miller, 1987). This includes prior research on the technology-
structure relationship (Miller et al., 1991). Decentralizing and complexifying structure
implies more elaborate communication, coordination, and control mechanisms; this in
turn requires an infrastructure that can be better enabled through information technology
(Huber, 1984; Leifer, 1988). Hence, more decentralized management and complex
administrative structures should lead to greater adoption of information technologies by
retailers (Cohn & Turyn, 1984; Miller & Toulouse, 1986; Raymond, Pare, & Bergeron,1993).
The second set of adoption factors is strategic in nature, identifying the level of
assertiveness, rationality, and interaction in business decision processes. These three
factors have emerged in the strategy literature as fundamental dimensions or derivative
constructs of the strategy concept (Miller, 1987; Venkatraman, 1989). The first
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dimension refers to the proactiveness of decisions and risk taking. The second one
concerns the planning and formulation of strategies. The third one refers to the
political/bargaining processes that bear upon decisions. Information technology has
become one of the key elements in the definition and realization of strategic objectives
(Vitale, Ives, & Beath, 1986). In an increasingly complex environment, organizations
must "align" their use of information technology with the implementation of their
strategic decisions (Chan & Huff, 1993). Thus, when they are more proactive, more
future/planning-oriented, and when more executives interact in strategy making, retailers
would be more apt to implement computer-based information systems resulting from or
in support of their strategy (Shrivastava & Grant, 1985; Schroeder, Gopinath, &
Congden, 1989).
The third set of factors thought to influence new technology adoption in small retail firmsare organizational, including size, sector, and status (independent or affiliated).
Organization theorists have found the first two contingency variables to consistently play
an important role in structure-technology-strategy relationships (Ford & Slocum, 1977;
Miller et al., 1991). One expects larger firms to have adopted more sophisticated
technologies (Dewar & Dutton, 1986; Raymond, Pare, & Bergeron, 1993). The same can
be said of firms in more information-intensive retail sectors, e.g. hardware as opposed to
clothing (Kimberly & Evanisko, 1981). Firms who become linked to banners or buying
combines, as opposed to remaining independent, would also be greater users ofinformation technology (Tornatsky & Klein, 1982). The greater technological
sophistication obtained by retailers who cooperate among themselves would tend to
reduce environmental uncertainty in terms of markets and competitors (Huber, 1984).
The seven factors of new technology adoption were chosen due to their fundamental
nature as descriptors of structure, strategy, and organizational contingencies. These
factors have also been identified as fundamental determinants of technology, both
theoretically and empirically, and all have been used previously in the small business
research context. Note that many of the organization theory and strategic management
studies cited here point to the interdependence of strategy and structure, and to the
contingent role of size and sector in this regard. However, given the focus and objectives
of this study, expected interrelationships between structure, strategy, and organizational
contingencies were not made explicit in the research model.
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No distinction was made between management and production technologies as indicators
of technological levels because in retailing, unlike manufacturing (Raymond & Pare,
1992), it is difficult to differentiate the two. In addition, the actual level of independence
or involvement in a group was not measured, even though some retailing groups (buying
combines, trade banners, coops, franchises) exercise more control over their members
than others. However, franchisees were excluded from the study because, in contrast to
the other groups, their independence is very restricted (Castrogiovanni, Bennett, &
Combs, 1993). In the Canadian province of Quebec, where the survey took place,
independent retailers and members of buying groups or coops are responsible for more
than 72% of all retail sales, at the expense of chains and megastores, whereas in the rest
of Canada and in the U.S.A., their share is much smaller.
RESEARCH METHODOLOGY
The survey was carried out by collecting data from a sample of small retailers in the food,
hardware, and ladies' garment sectors. Their names were obtained from the central
business data bank of Quebec's commission on health and safety in the workplace
(CSST). The survey was performed in two stages. First, 1,200 letters were sent out to the
addresses provided by the CSST, requesting an interview with the owner (4.8% of these
were returned due to improper addresses or out-of-business situations). Among the 232
(19.3%) who were willing to cooperate, a total of 79 retailers were selected for semi-
structured interviews in the field, with the help of a questionnaire. Using CSST data for
the entire 1,200-firm population, the 79 firms were chosen on a stratified sampling basis,
to be statistically representative of this population in terms of size and regional
distribution for each sector. This was verified through chi-square and t tests. The
questionnaire included 56 closed questions and six open questions, divided into four
sections: the firm's demographics (size, status, etc.), structure, computer hardware and
software, and strategy. A pre-test was done using three firms from each of the three
sectors. Interviewing was deemed preferable to mailing the questionnaire, due to the
technical or open nature of many questions, and to acquire more in-depth information.
Two main types of technology were distinguished in the survey: hardware for business
computing (computers), point-of-sales computing (computerized cash registers, whether
or not linked to a central processing unit), and tele-computing (electronic links with
outside firms, usually wholesalers); and software, assessed by the nature of the
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applications portfolio. The measures of hardware and software technology adoption, i.e.
the dependent variables, were adapted from previously developed instruments by Julien,
Hebert, and Carriere (1988) and by Raymond and Lorrain (1992). Two main dimensions
of structure--centralization and complexity--were assessed by measuring the managerial
hierarchy (number of managers excluding the owners(s)/all personnel) and the
administrative apparatus (clerical workers/all personnel), both measures previously
validated and used in a small business context (Paulson & Stump, 1979). Complexity was
also ascertained by the presence of a management committee (Julien, Hebert & Carriere,
1988). The same was done with the three principal components of strategy, namely
assertiveness, rationality and interaction. Miller's (1987) instrument was used to measure
strategic orientation (or proactiveness: reactive-proactive) for the first dimension,
organizational time-frame (or futurity: short-long term) for the second one, and strategic
decision making (individual-consensual) for the third one.
Table 1 shows the descriptive statistics of the research variables. Thirty-six percent of
firms operated in the food sector (grocery stores, butchers, etc.), 40% in the hardware
sector and 24% in the garment sector. They employed an average of 14.5 people
(excluding owners), including 2.5 office staff. In all, slightly over 50% of the businesses
were affiliated to a trade banner or buying combine, and 46% had a management
committee. Strategically speaking, they were fairly proactive (4.0 on a scale of 1 to 7),
had a medium time-frame (2.7 on a scale of 1 to 5), and shared the decision-makingprocess to a moderate degree (4.0 on a scale of 1 to 7).
ADOPTION OF NEW TECHNOLOGIES
The overall survey results show that 63 of the 79 firms questioned (79.7%) used at least
one computer-based technology (i.e. electronic cash registers), a higher number
TABULAR DATA OMITTED than the 71% forecasted by Collard (1989) for 1993 in the
United States. The percentage is higher in the food sector (92.8%) than in the hardware
(84.4%) and garment (57.9%) sectors. In all, 36 firms (46.2%) used only stand-aloneelectronic cash registers, 11 (14.0%) used cash registers linked to a central register, and
16 (20.5%) had a cash register system linked to a computer. Eight firms (10.0%) had only
a fax or telex, 31 (39.4%) maintained outside links by modem for batch data transfers or
financial transactions (with banks), and 21 (26.9%) maintained systematic outside links
through computers or terminals (EDI).
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The number of business computing applications varied from zero to four. Eight firms
(10.1%) indicated using four applications, 16 (20.2%) used three, ten (12.7%) used two,
and four (5.1%) used only one application. In all, 41 firms (51.9%) did not use any form
of business computing. Overall, the type of technology least used by sample firms turned
out to be business computing and related applications. The other two technologies were
more widespread, as only 15 firms (19.0%) did not have an electronic cash register (POS
computing) and 18 (22.8%) did not have an electronic link with an outside organization
(tele-computing). Table 2 summarizes mean adoption rates for each technology (using 5-
point sophistication scales).
DETERMINANT FACTORS OF NEW TECHNOLOGY ADOPTION
Shown in Table 3 is the intercorrelation matrix of the independent variables. Given its
highly significant relationship with five other factors, size was removed from further data
analysis to reduce problems due to multicollinearity (Huang, 1970). The same was done
with the decision-making variable, as it is strongly correlated with the other two strategy
variables. Note that after removal of these two variables, two intercorrelations
TABULAR DATA OMITTED greater than 0.3 remain, that is, firms in the clothing
sector and firms with a larger bureaucracy (administrative apparatus) are less likely to
have an affiliated status (r = -0.52, r = -0.35).
As hypothesized, differences in levels of hardware and software technology adoption byretailers are due to a number of organizational, structural, and strategic factors.
TABULAR DATA OMITTED
Shown in Table 4 are the results of stepwise regression analyses on the four technology
variables, revealing the determinant factors in each case. Retailers who adopt business
computing are less likely to be in the food sector and tend to be affiliated to a buying
combine or trade banner. They are more decentralized, i.e. show a higher ratio of
managers (managerial hierarchy), and are more likely to have a management committee.
Strategic factors do not seem to come into play here.
The adoption of POS computing is determined by a different set of factors. Clothing
merchants are less apt to employ this technology, as are firms with a larger ratio of
clerical personnel (administrative apparatus). In addition, firms with POS technology
have a longer organization time-frame. The use of tele-computing is mostly determined
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by the retailer's status as member of a combine or banner, as expected. Firms who have
implemented EDI are also more future-oriented than others, confirming Blili and
Raymond's (1993) conjecture.
Not surprisingly, hardware stores, with their greater information needs (e.g. for inventorymanagement), are the ones with the more extensive applications portfolio (software),
while more decentralized firms implement a more sophisticated management information
system. These results are in line with the technology-structure relationships found by
Raymond, Pare, and Bergeron (1993). Also, more proactive and future-oriented retail
firms implement a more extensive applications portfolio. This confirms the mutually
determining impact of strategy and information systems in the context of SMEs (Blili &
Raymond, 1993).
Table 4
Regression Analyses on the Four Technology Variables
Standardized betas(a)
HARDWARE SOFTWARE
Business Point-of-sales Tele-
Application Variable computing computing
computing portfolio
ORGANIZATION
Size (removed initially)
Sector
Food -.22 -- -- --
Hardware -- -- -- .22
Clothing -- -.32 -- --
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Status .36 -- .42 --
STRUCTURE
Managerial hierarchy .30 -- -- .28
Administr. apparatus -- -.24 -- --
Management committee .21 -- -- .23
STRATEGY
Orientation -