Abstract
The purpose of this article is to recount some highlights of a personal journey of a case study researcher. The researcher not only hopes to give a methodological and scholarly approach to the research but also intends to share some personal exciting and disappointing experiences during the journey. The article gives a detail on identifying the research problem, selection of the adequate research method, selection of the research organization, data collection, analysis and making sense of the data, publishing the results and extending research into post-doctoral research.
Keywords
Start of a Three-year Journey
The journey started in the year 2007 when the researcher joined the Fellow Programme in Management at Management Development Institute, Gurgaon, India. The academic world appeared very different from the action-oriented corporate experience in consulting. The researcher at Price Waterhouse Coopers had been a part of projects for companies making efforts to improve their processes through implementation of information technology.
In the first year of the academic endeavour, the researcher became aware of various terms in research like philosophy of research, the importance of being clear about the epistemological position taken in research and the relevance of having a research design. According to Nachmias and Nachmias (1976, pp. 77–78),
Research design is a plan that guides the investigator in the process of collecting, analyzing and interpreting observations. It is a logical model of proof that allows the researcher to draw inferences concerning causal relations among the variables under investigation. The research design also defines the domain of generalizability, that is, whether the obtained interpretations can be generalized to larger population or to different situations. (as quoted in Yin, 2006)
Before proceeding with the research design, it became essential to be clear of the epistemological position taken in the research. The term ‘epistemology’ comes from the Greek language, with episteme meaning knowledge and logos meaning theory (Grbich, 2007). According to Grbich (2007), there are four broad epistemological traditions that impact qualitative research within which claims for ‘truth’ have been made:
Positivism/empiricism Critical emancipatory positions Constructivism/interpretivism Postmodern and post-structural positions
Positivism/empiricism tradition views truth as absolute, values the unique aspects of scientific research and focuses on objectivity (knowledge of reality gained by a neutral and distant researcher utilizing reason, logic and range of carefully pre-tested research tools) and theory-testing that can distinguish between facts and values. Knowledge is viewed as something which can be deduced from careful processes of hypothesizing, variable identification and measurement within experimental designs, resulting in the identification of causality and predictions being made about ‘facts’ which have been properly evaluated by mathematical logic.
The constructivism/interpretivism position assumes that there is no objective knowledge independent of thinking, and reality is socially and societally embedded existing within the mind. This reality is changing and knowledge is constructed jointly by the interaction between the researcher and the researched through consensus. Knowledge is subjective, with multiple realities being experienced by different people differently.
Postmodernism views the world as complex and chaotic and reality as constructed and transitional that cannot be explained by grand narratives or metanarratives. Under this position, individual interpretation is paramount with there being no objective reality and truth and reality lying in meanings we construe regarding our own subjective perceptions of our life experiences.
Post-structuralism lays emphasis on language and is an important subset of postmodernism. Language is viewed as a system of signs and codes. Patterns provide meaning and all words are seen as having recognized meanings which could be learned. It was believed that absolute truth did exist. The focus was to understand reality through the use of logic and reasoning. Although the focus was on discovering objective reality and crafting measures that would detect those dimensions of reality, the aim was to refine the study through theory building. The research started with a conceptual framework, which was premised on the existence of a priori relationships within the phenomenon. These relationships were capable of being identified and tested via hypothetic–deductive logic and analysis and were the basis of generalizable knowledge that can predict patterns of behaviour across situations. In accordance with the positivism/empiricism tradition, the research was based on a priori framework established from the literature review. This framework was modified, and theory in the area of research extended based on the empirical evidence. Figure 1 traces the approach to research.
Identifying the Research Focus and the Research Problem
The researcher, during corporate experience, had seen companies make efforts to change both incrementally and radically. The current dynamic environment and foreign competition had put pressure on them to innovate with respect to products, services, their processes and business models. In their effort to differentiate themselves, they were not only emphasizing on internal R&D and experimentation but also entering into collaborative alliances. For many firms, technological innovation was the primary means of competing in the knowledge-intensive twenty-first century.
The researcher was also involved in an earlier research linking innovation to the knowledge base of the organization. The research highlighted the importance of various critical factors that enabled the acquisition and application of knowledge to promote innovation. It mentioned that implicit knowledge can be managed indirectly by managing an organization’s culture, structure, technology and leadership (Dasgupta, Sahay & Gupta, 2009).
Linking to the corporate experience, it could be seen that technology had a profound impact on the development of organizations. Organizations were using technology as the primary source of competitive advantage. The rise of information technology and telecoms also enabled the rise of global networks within the same firm and between different firms. The long-run competitive position of an organization was therefore dependent on how prudently organizations managed their technological asset bases. Organizations, however, differed as they developed competencies in different technologies. They also differed in the way they exploited or deployed the available/acquired technology.
The pattern of choices which firms make with respect to technology is reflected in their technology strategy. It was evident that technological innovation and strategic use of technology can play a central role in providing both comparative and absolute advantages. The vast empirical literature in the field of technological innovation and technology strategy has ignored the role of various dimensions of technology strategy in the technological innovation process of an organization. How organizations develop a coherent strategy for the acquisition and deployment of technology as an instrument of the technological innovation process of the organization is a subject which had not been researched. Which are the elements of an effective technology strategy for technological innovation? There have been more investigations of a general nature in technology strategy rather than that of specific technological dimensions. It was felt that research was necessary to understand how the various dimensions of technology strategy guided the acquisition, deployment and abandonment of technology to promote innovation.
In the process of reviewing literature in the field of technological innovation and technology strategy, it was realized that past research was also hinting at the importance of organizational factors for both technological innovation and technology strategy. Therefore, study of the various organizational factors also formed a part of the scope of research.
First, the research aimed to describe how technological innovation in an organization was driven by its technology strategy. Second, the study explored the organizational factors that supported technology strategy to promote technological innovation. Finally, the study explored the business/operational dimensions that get affected by technological innovation.
Looking at the limited time and resources at disposal, the researcher was realistic with respect to the scope of the research. As a beginner in the field, and being very well aware of the limitations, groundbreaking research was not benchmarked as research outcomes of the study.
Building the Research Framework/Penning Down the Research Objectives
According to Anderson and Ayden (1994), two approaches might be taken when using existing theoretical constructs to guide the theory-building research. In the first, the researcher works within an explicit conceptual framework which ‘consists of a selection of concepts and relations among them, grouped so as to enable its users to easily see the major concepts simultaneously in their relations to one another’ (Kochen, 1985, p. 93).
The research framework, therefore, serves as a foundation for making explicit theoretical statements (Miles & Huberman, 1994). It provides the groundwork for design and completion of the study. It helps to analyze and interpret data and then tie the findings back into the literature derived from the theoretical framework (Bettis & Mills, 2006; Fowler, 2006; Harris, 2006; Karpiak, 2006; Lugg, 2006; Merriam, 2006; Mutch, 2006).
Some writers reject the imposition of any a priori theoretical frameworks at the outset. In the second approach, the researcher is not constrained by prior theory and uses the project to develop relevant theory, hypothesis and concepts (Glaser & Strauss, 1967; Strauss, 1987; Strauss & Corbin, 1990).
Although Eisenhardt (1989) suggests that theory-building research should begin as close as possible to no theory and no hypothesis to test, she also stresses that it is quite impossible to achieve the ideal of a clean theoretical slate.
The first approach was adopted for the study. Using the research questions as a guide, a conceptual framework was developed to group the constructs to study the role of technology strategy in technological innovation, the role of organizational factors in technology strategy and the different criteria adopted to evaluate the success of the innovation. According to Eisenhardt (1989), although early identification of possible constructs or factors allows them to be explicitly measured in interviews, it is equally important to recognize that the identification of constructs is tentative in theory-building research.
A wide variety of theories of the firm have been postulated that can be broadly classified as economic, behavioural and cognitive theories. Economic theories brought in the concept of the firm aiming at lowering the costs of transactions (Coase, 1937; Williamson, 1985). Behavioural approaches have put forth the views that the firm exists as a coalition of diverse goals (Cyert & March, 1963) and bundle of resources (Penrose, 1959; Wernefelt, 1984). Cognitive theories broadly deal with decision-making and choices, culture and knowledge-based view.
Of the various foundation theories guiding research in diverse areas, the resource-based view, transaction cost theory, resource dependence theory and dynamic capabilities model were identified to explain the role of technology strategy in technological innovation. Figure 2 depicts the initial conceptual model.
The operationalization of the key constructs, technological innovation, technology strategy and organizational factors, was derived from literature review. The technology strategy framework proposed by Burgelmann and Rosenbloom was used to explore technology strategy through the dimensions of substance and enactment. Tables 1, 2 and 3 give the operational summary of the various constructs.
Substance—Operational Summary
Enactment—Operational Summary
Organizational Factors: Operational Summary
Selecting the Adequate Research Method
The next step, selection of an adequate research method was a difficult and perilous task. Philosophical and personal biases affect the decisions with respect to the methods. The researcher was aware of her capabilities and inclination to conduct an exploratory study. Getting an in-depth understanding of a phenomenon and how critical decisions were taken excited the researcher more than the numbers.
Quantitative and qualitative methods have been used in empirical research on the resource-based view (RBV) (Barney & Arikan, 2001; Hoskisson et al., 1999). Although there is no perfect connection between purpose and approach, quantitative research has been directed more towards theory testing while qualitative research has been concerned with theory building. Thus, while most quantitative research is confirmatory, most qualitative research is exploratory (Azorin, 2007).
There are various approaches in qualitative methods. Qualitative designs are naturalistic to the extent that the researcher does not attempt to manipulate the phenomenon and its participants for purposes of evaluation and the study is based on naturally occurring activities and processes. The evaluation approach is inductive to the extent that a researcher attempts to make sense of situations without imposing pre-existing expectations on the setting. Inductive design begins with specific observations and builds towards general patterns. Abductive reasoning is a method of logical inference where an inquirer considers a set of seemingly unrelated facts with an intuition that they are related. Abductive reasoning links empirical observation with imaginative interpretation, but it does so by seeking theoretical accountability through returning to the empirical world (Bryant & Charmaz, 2008). Qualitative designs are holistic to the extent that an attempt is made to understand the phenomenon and situations as a whole. It assumes that the whole is greater than the sum of its parts (Patton, 1987).
According to Patton (1990), qualitative research is adequate where the focus is on processes (how something happens) rather than on the outcomes or results obtained. For example, in RBV, it is interesting to know how resources, capabilities or competencies emerge and develop inside the firm (Azorin, 2007). The underlying logic in qualitative research is inductive as it tries to generate new theories and new explanations (Gibbs, 2007).
In recent years, however, the debate between quantitative and qualitative methodologies has softened. The importance of matching appropriate methods to questions and choices has been accepted over the need to advocate any single methodological approach for all situations (Patton, 1987).
Because the objective was to understand and not to measure the phenomenon, qualitative paradigm of research was adopted. The study was based on abductive reasoning where the study was started with an intuition of a possible relationship between technology strategy and technological innovation. As an end result of the study, it was hoped that a possible description of the role of technology strategy in technological innovation could be inferred.
According to Godfrey and Hill (1995), qualitative methodologies such as multiple case studies, event histories and ethnographic inquiries might be the best way forward in observing the effects of an otherwise unobservable, idiosyncratic effects on business strategy and performance, such as those predicted by the RBV (cited in Azorin, 2007). Hoskisson et al. (1999) point out that the case study methodology, because of its capability to provide much richer information about the firm’s idiosyncrasies, is appropriate for RBV research.
Yin (2003) explains that the case study research strategy is most likely to be appropriate for ‘how’ and ‘why’ research questions because they deal with operational links needing to be traced over time, rather than mere frequencies or incidence (Pare, 2004). He defines the scope of case study as ‘an empirical inquiry that investigates a contemporary phenomenon within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident’ (p. 13). Case research is therefore useful for the following conditions:
When a phenomenon is broad and complex. Where the existing body of knowledge is insufficient to permit the posing of casual questions. When a holistic, in-depth investigation is needed. When a phenomenon cannot be studied outside the context in which it occurs.
A case study can be technically defined as ‘an empirical inquiry in which the number of variables exceeds the number of data points’ (Yin, 2006). According to Eisenhardt (1989), ‘Building theories from case studies is a research strategy that involves using one or more cases to create theoretical constructs, propositions and/or mid-range theory from case-based, empirical evidence’ (as quoted in Eisenhardt & Graebner, 2007).
In case study method, a choice has to be made between a single and a multiple case design. A single case study is an appropriate design when it represents a critical case in testing a well-formulated theory, or an extreme or unique case or a revelatory case (Yin, 2003). Neither of these conditions is applicable to this research. Therefore, a multiple case study design was chosen.
Multiple case studies also provide a stronger base for theory-building (Yin, 1984). Moreover, comparison groups provide simultaneous maximization or minimization of both differences and similarities of data which is vital for discovering categories and for developing and relating their theoretical properties which are necessary for further development of emergent theory (Glaser & Strauss, 1967). The research questions indicate a cross-case analysis. According to Eisenhardt (1989, p. 541), ‘the juxtaposition of seemingly similar cases by a researcher looking for differences can break simplistic frames’. Past literature shows that around 75 per cent of researchers have used case study research to study technology strategy of organizations. Therefore, it was planned to do a multiple case design that would not only allow the studying of the phenomenon but also the drawing of similarities and differences across the cases.
The design followed was predominantly sequential with one case study following the other. The advantage of sequential approach is that the selection of each case and some of the issues examined can be informed by puzzles identified in earlier cases (Vaus, 2006). According to Vaus (2006), case studies might have a retrospective or prospective time dimension. Whereas retrospective design involves tracking of past events, a prospective design involves tracking changes in forward over time. Because of time and resource constraints, a retrospective approach was adopted to build a clear and detailed picture of the sequence of events that took place.
Selecting the Study Organization
The next task was to select the ‘unit of analysis’ for the study. According to Markus (1989), practical significance of the findings for the theory rests on the study of appropriate unit of analysis. A clear definition of the unit of analysis helps defining the boundaries of a theory. According to Yin (2003), definition of the unit of analysis must be related to the way the initial research questions are defined and the generalizations which are required at the completion of the project.
However, since the aim of theory-building research is building theories and not testing of theories, theoretical sampling is most appropriate. Theoretical sampling means that the cases are selected because they are particularly suitable for illuminating and extending relationships and logic among constructs (Eisenhardt & Graebner, 2007).
In the study, the research questions deal with studying the role of technology strategy in the technological innovation process in an organization. Hence, the unit of analysis for the study was an organization.
Although the study started, with the unit of analysis being an organization, preliminary visits to the field made the researcher revise the definition of unit of analysis for the purpose of the study. All technology decisions flow from the corporate level, and design and formulation of technology strategy is the domain of the top management (the chairman, chief executive officer, chief technology officer and the board of directors); for the purpose of the study, the unit of analysis has been defined as an organization with a distinct top management team.
The theoretical framework and research questions guided the selection of the organizations which would form a part of the study. Because the intention was to study technological innovation, it was essential to select organizations which had taken initiatives to come out with either new or improved products and services. ‘Will I get access into the organization and will the organization be willing to share information?’ It was the top most of all questions the researcher had when selecting the organization. Power is one of the core parameters for the growth and development of any economy. It can impact the whole economy and any innovation in this sector will have an exponential impact on other industries. India is power deficient and technological innovation and appropriate strategy would improve the output with the same resource inputs. Last but not the least, the Indian power industry has grown substantially since independence, from an installed capacity of 1362 MW in 1947 to 146752 MW 1 as on 31 March 2008. The industry has an immense potential for growth with the Ministry of Power setting a target of ‘Power for All by 2012’. 2 Along with this quantitative growth, the Indian power sector has also achieved qualitative growth. This is reflected in the advanced technological capabilities and the large number of highly skilled personnel available in the country. 3 Reference from one of the professors also helped in getting access into the organizations.
Although initially the scope was identified as studying two organizations, each from the power generation, transmission and distribution sector, due to time and resource constraints and also as advised by the research committee, the scope was narrowed down to studying the distribution sector in the Indian power industry. First, it was felt that the distribution segment was the cutting edge of the power industry, because the commercial viability and customer responsiveness of the segment was the key to setting right the other two segments of generation and transmission. The supplier–consumer interface is reflective of the nature of this industry. In the words of Mr Rakesh Nath, Chairperson, Central Electrical Authority, ‘Unless the distribution sector improves the whole power sector cannot improve.’ 4 Second, the literature review did not have any similar study in the power distribution sector. Last but not the least, the Indian distribution companies had taken various initiatives in order to turnaround the dilapidated distribution sector of the country.
Limiting the study to the power distribution sector also helped to control the extraneous variations (Eisenhardt, 1989). Through the multiple case designs, it was hoped that the theory in the field of technology strategy and innovation would be extended and also similarities and differences across the different cases would be drawn.
It was decided to restrict the study to four distinct organizations in the power distribution sector: Bombay Suburban Electric Supply (BSES) Rajdhani Power Ltd. (BRPL), BSES Yamuna Power Ltd. (BYPL), North Delhi Power Ltd. (NDPL) and Dakshin Haryana Bijli Vitran Nigam (DHBVN). Although the study was in the four organizations, for the purpose of analysis and reporting of findings, BRPL and BYPL have been treated as one strategic unit—BSES. The study of the three units of analysis has formed a part of the case study research in the works of Stoddart and Jarvenpaa (1995), Pare et al. (1997) and Gordon and Tarafdar (2007). BSES, Delhi, comprising BRPL and BYPL , was chosen as the first study organization. BSES distributes power to 22.2 lakh consumers, about two-thirds of Delhi, and has its mission to be amongst the most admired utility companies in the world. The company had also taken various initiatives to fulfil its mission. Although BRPL and BYPL are registered as two separate companies, they are subsidiaries of the same company Reliance Energy, and both of them share predominantly the same board of directors, a common chief executive officer (CEO) and a common chief technology officer. Although they are two different legal units, they are one as a strategic unit. The following remarks by senior management of the two companies reflect the same. ‘IT, MIS, Finance, procurement etc. are common for both companies.’ ‘They are basically two entities operating as one virtual organization.’ Being under the same management and having a common technology strategy, they were treated as one unit of analysis, BSES Delhi.
Yin (2003) has suggested the concept of embedded sub-cases. However, for the purpose of the study, the two firms, having a common technology strategy and taken identical technological initiatives in their areas, were clubbed under a common umbrella of BSES, Delhi. As a consequence, falling into the trap of narrating repetitive information was avoided.
NDPL was chosen as the second organization. NDPL, apart from supplying power to one-third of Delhi, had won the prestigious Silver ‘National Award for Meritorious Performance’ for 2004–2005 and 2005–2006 in power distribution and also had won the Asian Utility of the Year 2008 award.
DHBVN, a state-owned power distribution utility that distributes power in the state of Haryana, was chosen as the third organization. It was felt that choosing a state-owned distribution company would help to draw out differences across cases regarding decisions with respect to technology for promoting innovation.
Identifying the Key Informants
Before going for field study, it was essential to identify who would be the key informants; that is, employees in the organization who would be able to answer questions related to the organization’s technological initiatives and various technology decisions. The researcher started with interviewing employees from the study organizations who were also participants of the Energy Management Program at the institute.
Purposeful and chain (Patton, 1990) sampling was done in order to conduct interviews with chief technology officer, vice presidents, general managers, senior managers and heads of groups, that is, people who were either involved with/or were aware of technology strategy decisions. As the researcher had got reference from the participants of the Energy Management Program, approaching the key informants became an easier task. Interviewees were also selected on the basis of references by employees the researcher met during visits to these organizations. According to Patton (1990), the power of judgemental sampling lies in selecting information-rich cases for in-depth analysis. According to Lincoln and Guba (1985), a few members are used to identify others in the group until a point of redundancy is achieved. Not only does the technique provide more convincing evidence of the credibility of the theory developed but it also allows for answering the question, ‘When can I stop sampling?’ Interviews were also conducted with randomly selected employees.
Table 4 gives the list of key informants.
Proceeding with Data Collection
The researcher started with designing a case study protocol detailing the agenda to be followed for pursuing the line of inquiry and the interview guide, containing the specific semi-structured questions to be asked during the course of study.
The case data were collected primarily through interviews based on semi-structured questionnaires (mentioned in the case study protocol). Semi-structured interviews ensure that all information is obtained, while at the same time giving participants the freedom to respond and illustrate concepts (Yin, 2003). The interview process consisted of initial in-depth interviews of about 60–90 minutes and shorter follow-up interviews with respondents and additional personnel to clarify various issues. All the interviews were recorded. In addition, follow-up questions were asked via phone or e-mail where clarification was required. In order to mitigate bias in the data collected, interviews were conducted with informants from different hierarchical levels, functional areas and groups who could give diverse perspectives on the phenomenon (Eisenhardt & Graebner, 2007). There were a number of short information-gathering discussions with other employees in the company. Generally, these were conducted to gain information about the various organizational factors, as the employees were not involved in the strategic issues that were the topic of research. The number of informants interviewed in each organization followed the notion of ‘theoretical saturation’ suggested by Glaser and Strauss (1967, pp. 61–62). Interviewing additional people was stopped when the researcher started hearing the same narrative repeated over and over (Harris & Sutton, 1986). Data were also collected through observations during meetings and collection of archival documents during field visits. The archival documents and news articles collected and the various business reports available on the web also provided precious information which was used to compare the responses of the interviews.
Key Informants
Scheduling the time with senior management and receiving their undivided attention during the interview was a big challenge. While some took the interviews seriously, there were a few who felt that the interviewing process was just a formality and anything could be written in the report. One or two felt that their day’s work at the job was getting hampered by the researcher’s questions.
An interesting incident happened, when after travelling for two and a half hours to meet an interviewee, the researcher had to answer a lot of the interviewee’s questions. After the allotted time for the interview, he asked, ‘Are you feeling angry and frustrated at me. I want you to feel so, because in my personal opinion if a researcher goes back feeling content and satisfied it is the end of his/her quest.’ The researcher had no answer but had to smile and thank him for sparing his time.
The researcher is however indebted to all the personnel who took time out to provide information critical for the study.
Analyzing and Making Sense of Data
Qualitative research is a matter of the researcher’s interpretation of what the respondents and participants say and do (Gibbs, 2007).
Theoretical propositions were followed which led to the research questions and the proposed framework in analyzing the case study evidence. A separate folder was created for each firm. All the recorded interviews were played and replayed and transcribed in word documents. These transcribed interviews were thereafter coded. According to Charmaz and Mitchell (2001), coding provides shorthand synthesis for making comparisons between different people, objects, scenes or events, as well as data from the same people, scenes, objects or type of event and incident with incident (as quoted in Gibbs, 2007). The coding procedure suggested by Miles and Huberman (1994), and open coding used in grounded theory (Strauss & Corbin, 1990) guided me in the process of creating ‘conceptual labels’ for the phenomenon observed. A priori codes were used to organize and retrieve segments of text for easy interpretation and search. A combination of descriptive and inferential codes was used to serve the purpose. While the former were used to describe a particular class of phenomenon, the latter were used to interpret some ‘backstage’ motivation into the text. The codes helped to assign meaning to the descriptive information compiled during the study. For example, interpretation of a respondent’s future expectations from a particular technology decision helped to create one of the technology substance categories of ‘Tactical’/‘Strategic’.
While the researcher started with an initial coding scheme based on the conceptual framework, list of research questions and other theoretical considerations, other codes were adopted during the analysis process (Kiel, 1995). Conceptual labels were created on the basis of themes appearing in the sentences. The names chosen for the labels were the ones which seemed most logically related to the data they represented. These conceptual labels were grouped together to form categories pertaining to the substance and enactment of technology strategy. Marginal and reflective remarks (Miles & Huberman, 1994) were mentioned on the right-hand side of the transcribed notes. They were used to represent insights and interpretations of the information captured through the interviews.
Table 5 illustrates a few interview comments and the codes identified from them.
Interview Excerpts and Coding
Conceptually clustered matrices, with defined rows and columns, based on the constructs/dimensions appearing in each case, were used to display and analyze data. A separate table that summarizes the evidence for each theoretical construct is a particularly effective way to present case evidence (Eisenhardt & Graebner, 2007). According to (Miles & Huberman, 1994), a conceptually clustered matrix through its rows and columns bring together items that ‘belong together’ either conceptually or empirically. While in the former case the analyst might have some a priori ideas about items that derive from the same theory or relate to the same overarching theme, in the latter case the information given by the informants ties various concepts together. Summary tables that summarized the case evidence were used to complement the story description of the text and also to emphasize the empirical grounding of the theory.
After displaying and analyzing data from separate tables, the researcher proceeded with analyzing each technological initiative with respect to the conceptual labels discovered during open coding. These labels also represented the substance of technology strategy. Each initiative was also analyzed with respect to the conceptual labels discovered for the enactment of technology strategy. While acquisition comprised labels representing the various technology acquisition strategies adopted by firms, deployment comprised labels representing the strategic focus of firms in deploying the various technological initiatives. The framework proposed by Burgelmann and Rosenbloom was refined on the basis of labels and categories created from the coding procedure.
The researcher had used cross-tabulation in one of her previous research articles for clustering and analysis of quantitative data. She was seeking a similar technique that would help to analyze qualitative data and identify patterns. According to Miles and Huberman (1994, p. 249), clustering is a tactic that can be applied at many levels to qualitative data: at the level of events or acts, of individual actors, of processes, of settings/locales, of sites or cases as a whole. It helps to inductively form categories and sort events, processes, sites, etc. into those categories; it relies on aggregation and comparison. It helps to understand the phenomenon better by grouping and then conceptualizing objects that have similar patterns or characteristics. To draw and verify conclusions regarding the relationship between technology strategy and technological innovation, the different technological initiatives taken by the organizations were clustered according to the substance and enactment of technology strategy. Plotting of individual case data was followed by plotting of data of all the cases onto the technology strategy framework. This helped in cross-case comparison and also to discover patterns with regard to the choices the firms make for appropriation and deployment of technology for the purpose of technological innovation.
The matrix in Table 6 illustrates the clustering approach followed for the different innovation initiatives taken by the three firms.
A Sample of Clustering Innovation Initiatives on the Technology Strategy Matrix
Contribution from the Research Leading to Limitations and Directions for Future Research
The journey culminated with submission of the thesis and viva by external examiners in 2010. The study helped to propose a comprehensive model linking technology strategy to technological innovation. Figure 3 gives the refined model.
The model has been refined so as to depict the complete innovation process—problem recognition, idea generation, selection of technology, development of solution and implementation. Technology strategy has been depicted through the two dimensions—substance and enactment (acquisition and deployment of technology).
The study helped to extend literature in the following ways:
It helped to explore the variations in technology strategy for technological innovation of different firms in an industry. It helped to document the relationship between different technological innovations and technology strategies of different firms in the power distribution industry. Currently, there is no similar study in the power distribution industry. It helped to identify the different dimensions of technology strategy that impact technological innovation in firms. Currently, the evidence of the relationship between innovation and technology strategy is limited. In short, the study helped to capture the Whys and Hows of technological innovation in the Indian power industry. It helped to identify patterns of technology choices supporting different technological innovations. The study helped to extend the Burgelman and Rosenbloom framework by operationalizing in a new industry domain—the power distribution sector.
The above does not mean that there were no limitations attached to the study. Mentioned below are some of the limitations of the study:
The study examines only the power distribution industry, which would raise the question of generalizability to other industries. The results would, therefore, have to be interpreted with caution. The data have been collected from the Indian power distribution industry and the results might not apply to power industry outside India. The study has been conducted with selected dimensions of technology strategy and technological innovations which were identified during the course of the study. Therefore, the study may offer an incomplete picture of the relationship between technology strategy and technological innovation.
The above limitations were used to identify directions for future research. They are as follows:
The study can be extended to other industries and the model tested to understand the variation in innovation practices and technology strategies between different industries. The study can be extended to understand the variation in technological innovation and technology strategies of organizations belonging to different industries which differ in terms of dynamism and level of competition. Such a study might suggest different dimensions of technology strategy. Further research could be extended to see the interrelationship of technology strategy of multiple industries of a conglomerate. The study can be extended to industries in different geographical locations. The model can also be tested out quantitatively to measure the impact of different dimensions of technology strategy on technological innovation. The proposed interface between the taxonomies of technology strategy and technological innovation can be quantitatively tested out.
Learning from Phase 1
The case study research helped the researcher to go through the rigour of a qualitative researcher with respect to collection and analysis of data. However, it also made the researcher realize the additional burden that a qualitative researcher carries with respect to proving the quality, validity and generalizability of the research. Concerns are raised about the subjectivity of the researcher, multiple perspectives and multiple ‘truths’ depending on different points of view.
To maintain construct validity, it was ensured that employees at different levels were interviewed and the interview data were supplemented by reports, presentations and other archival information shared by participants. Data were also collected from websites and press articles. It also becomes essential that the information collected from different sites is assimilated and sent to the key informants for verification. Explicit operationalization of the constructs also helps to proving construct validity.
Internal and external validity are other aspects which are questioned in qualitative research. Internal validity was ensured by analyzing the data based on theoretical propositions and rival explanations. Different bodies of literature were used to interpret the findings. External validity was maintained by conducting multiple case studies of different organizations, using literal replication logic for selection.
Reliability of research was ensured by using a case study protocol to conduct multiple case studies.
Challenge in Getting Qualitative Research Published
The research journey also involved the tussle in trying to get the research published. It started with identifying journals that accepted qualitative research and also had technological innovation/technology strategy as one of the broad themes of discussion. The fact that the journals were better convinced with quantitative results was soon becoming clear. Although the number of journals that have started accepting articles based on qualitative research is increasing, the number of journals accepting quantitative research still outnumber the former.
What kind of research is required to make a ‘contribution big enough for a journal to publish it’ is still a mystery. The response from journals that the researcher has got used to is, ‘Your contribution and paper does not ensure a global readership. We regret to say that we have to reject your paper. We hope this decision does not affect your future contributions to the journal.’ In fact, a question that the researcher has often raised to her professors is, ‘Are journals biased against research from India?’
Ironically, one of her articles after having gone through various round of reviews with a Category B journal, ‘I’ll keep the name of the journal a secret’, and found suitable for publication by the area editor, was rejected by the journal editor. When the researcher wrote to the journal editor, the reply was, ‘We need to take a relook at our internal systems and ensure that no Area editor directly writes to the author.’ A superb reply after sitting on the article for almost a year!!
The researcher is extremely grateful to a few journal editors who are trying to promote research from emerging markets. Many of her research articles’ journey of being read globally have started with them getting accepted and published by these journals.
Extending Qualitative Research to Mixed Methods Research
During the next phase, the researcher picked up a couple of limitations from the first phase and extended the qualitative research findings to a survey-based research. The propositions laid down in the first phase were developed into hypothesis and tested through linear regression. In the second phase of the study, a structured questionnaire was designed to collect quantitative data. Questions for multi-item constructs were developed for use with five-point Likert-type scales ranging from ‘strongly disagree’ to ‘strongly agree’. The survey was administered to 100 randomly selected employees from different organizations in both manufacturing and services sector. In order to make the results more generalizable, respondents from different industries were chosen.
Conclusion
The objective of this article was to narrate the journey of a qualitative researcher from the stage of selecting a research problem to the stage of analyzing the research results and documenting the contribution from the research. In the process, the researcher has tried to give an account of the challenges faced, the learning from the research and various critical aspects that a researcher needs to take into account.
Footnotes
Acknowledgements
The above article has been written out of experience gained as a researcher at Management Development Institute. I am grateful to my thesis committee Professor A. Sahay, Professor R.K. Gupta and Professor Atmanand for their support and guidance.