Issues in Management Accounting Research - Coursework Example

Issues in Management Accounting Research Name: Tutor: Course: Date: Weaknesses of two-stage models The two-stage model adoption, according to Kennedy and Fiss (2009), is related to motivation to achieve gains and opportunity framing in the early stage. It is related to motivation to avoid gains and threat framing when adoption is in later stages. However, criticism has been leveled against the conventional two-stage model over the argument that space and time separates the social and economic motivations. This model has been regarded by a number of authors as having major weaknesses. First, indirect testing of motivations to drive adoption influences substitution of legitimacy for efficiency instead of direct assessments (Kennedy & Fiss, 2009; Donaldson, 1995). Second, instead of providing of institutional processes, existing evidence supports the absence of economic and technical determinants of adoption (Scott, 1995). Similarly, Staw and Epstein (2000) observe that many studies have failed to strike a difference in adoption motivations among later and early adopters based on the two-stage model. This means that the pattern of adoption explains the conflicting and multiple circumstances that include social learning shown in the model. For example, later adopters understand what works more than earlier adopters and that is why, to a lesser extent, they desire to experiment with innovations. Third, conventional two-stage model adopters are limited in scope and only focus on achievement of economic gains while failing to argue that early adopters may pursue social gains such as attaining higher status or distinguishing themselves. Fourth, the model separates social and economic motives for adoption while sharply differentiating mimicking and rational adoption behavior (Kennedy & Fiss, 2009). Fifth, it is obvious that the timing of adoption remains unexplained, yet early or late adoption timing is assumed to explain the gains or losses behind adoption motivations. Decision makers will likely adopt an innovation that is late in the diffusion process to avoid losses and not to achieve gains and not as argued by the conventional two-stage model. Finally, the model assumes that the relevant predictor of adoption motivations is adoption timing but in the current debate, different circumstances in different firms affect adoption of diffusing innovations (Staw & Epstein, 2000). Current authors posit that adoption decision-making potentially creates diverse outcomes such as implementation and adoption of innovations among firms. The conventional two-stage model is seen as neo-institutionalist based on the theory isomorphism and needs to be expanded in scope (Lounsbury, 2008). Indeed, the model is short of institutional literature that currently includes heterogeneity and change in the study of diffusion (Chandler & Hwang, 2015). Contributions of management accounting innovations (MAIs) to the body of research At the firm level, the adoption of innovations has been influenced by firm characteristics and general contextual factors that prevail in this area of research. Researchers of management accounting not only draw on the new-institutional diffusion perspective but also new-institutional theory defined by the management fashion variant. A novel perspective on adoption has been shaped by the dynamic relationships between innovation characteristics and organizational culture, and how it relates to adoption timing and motivation (Cadez & Guilding, 2008). The study of Management Accounting Innovations (MAIs) signifies the onset of complex relationships between adoption and firm characteristics. Although this aspect has been assumes a static and direct relationship, it had been tested in previous management accounting research (Al-Omiri & Drury, 2007). Brown et al. (2004) helps to explain the weak link between the adoption of innovations and contextual factor findings in previous management accounting. The study of MAIs has identified Balanced Scorecard (BSC) not only as a mere collection of non-financial and financial measurements but also a translation of strategies of business units into a linked set of measures. While it defines the long-term strategic objectives and mechanisms to achieve feedback, it is possible to obtain feedback on those objectives (Kaplan & Norton, 1996). Innovative companies manage their strategies over their long run using the scorecard as a strategic management system (Kaplan & Norton, 1996). Benders and van Veen (2001) argue that the BSC has a lower degree of interpretative viability compared to Activity based costing, and Strategic Management Accounting (SMA), making it more clearly defined than other MAIs conceptually. Since its introduction, the development of ABC has been highly dynamic (Jones & Dugdale, 2002). Indeed, activity-based costing has developed a time-driven model and an activity-hierarchy model from being a full costing model (Kaplan & Anderson, 2007). The research study shows that SMA is an umbrella concept that considers the initial ideas of other MAIs such as the BSC and Activity Based Costing. However, how SMA should be understood remains unclear (Malmi & Ikäheimo, 2003) as the BSC concept has been dynamic since its introduction. Compared to that of other MAIs, the BSC has been relatively stable over time and its development has been less radical. Innovation diffusion as found in the new-institutional literature highlights the aspect of values and beliefs embedded in innovations as well as organizational culture (Love & Cebon, 2008). Because of perceived losses and social and economic gains, Kennedy and Fiss (2009) argue that the perspective taken by late and early adopters could be motivated at the same time to adopt. This research is an extension of previous work that presented and tested models such as the conventional two-stage model and the new institutional theory models to suggest a dynamic interplay between motivations for adoption, innovation values and beliefs and organizational culture. As a result, over time, they influence adoption decision-making on the unfolding diffusion. Specifically, the study of management accounting provides an in-depth understanding of late adopters and early adopters and answers the questions as to why certain firms are non-adopters and adoption motivations for them differ. These insights add credible support to the literature on new-institutional theory by questioning the basic assumptions validity of the influential two-stage diffusion model. For example, late adopters act to increase their legitimacy while early adopters seek economic benefit. This confirms the observation of Colyvas and Jonsson (2011) that adoption timing is a predictor relevant to the adoption motivation. Although current debate on early and late adoption fails to explain the adoption of a diffusing innovation, Chandler and Hwang (2015) shows that it can occur in different circumstances for different firms at different times. The study on MAIs contributes to the growing new-institutional literature studies of diffusion by responding to questions related to heterogeneity and change (Lounsbury, 2007). These include theory of isomorphism and neo-institutionalism found in two-stage model (Lounsbury, 2008). Adoption decision-making influences diverse outcomes on the implementation and adoption of innovations among firms. This study by Ax and Greve (2017) believes that the models discussed add to current explanations of organizational heterogeneity and diffusion literature on compatibility and factors hindering adoption. Firms in a collectivity, as argued by the model of Love and Cebon (2008), adopt innovation based on distinct motivations. For example, late adopters respond to institutional pressures while early adopters are motivated by compatibility. The arguments also explain why incompatible firms reject innovations as some compatible firms reject innovations in late stages and early stages. The study findings shape management accounting research through deeper understanding on the influence of incompatibility and compatibility on adoption decision-making. Research on MAIs elaborates graphics (Free & Qu, 2011), design characteristics (Drury & Tayles, 2005), and rhetorical elements (Ax & Bjørnenak, 2005). Empirically, the study on MAIs illustrates the culturally linked beliefs and values as significant in broadening the notion of MAIs. The issue of MAI adoption showcased in this study enhances the readers’ knowledge and understanding of the misfit or the role of fit between the values and beliefs and organizational culture linked to the implementation and use of innovations and innovations within firms. More specifically, the extent of use and implementation of innovations is seen in the role of fit or misfit related to issues as the degree of satisfaction or dissatisfaction and continuing or abandonment existence of innovations. This ensures achievement of non-financial and financial benefits using innovations. The compatibility idea explaining the adoption behavior is another implication for research by referencing firm characteristics and MAI characteristics. These findings show that firms could be incompatible with another but at the same time compatible with one innovation. In the studies of adoption, research support innovation characteristics and the relevance of considering both firm characteristics. Kennedy and Fiss (2009) argue that the framing of interpretations of innovation adoption could arise from situations of perceived threats of losses or perceived opportunities for gains. In such situations, it adds to the understanding of the interpretations of new institutional theory on adoption of innovations. On the other hand, additional research is needed apart from adoption motivations discussed in the Kennedy and Fiss (2009) model. New research will clearly explain and illustrate the need to interpret adoption situations and understand the factors that lead organizations avoid threats or pursue opportunities. The suggested findings on incompatibility and compatibility show that adoption motivations a firm’s organizational culture related to innovations that are compatible or incompatible. Research on MAIs is interesting although in-depth research is required to better interpreting adoption situations and understand the specific mechanisms involved. Studies on innovations have contributed immensely to literature by adopting an innovation depending on the condition and provide findings that suggest the need to make decisions on the level of perceived gains. The level of perceived threat or adoption is adequate to incur losses from non-adoption. Perceived levels of gains and losses have an association with adoption motivations. Limitations of the study and areas of improvements This empirical investigation on the study on MAIs has a number of limitations which should be considered during interpretation of results. To start with, manufacturing firms in Sweden were the only ones that formed the sample of the study. This makes it difficult to generalize the findings to other industries and countries. The industry structure and the nature of competition in previous research may differ country to country or industry to industry (Chang et al., 2003). As a result, there is limited knowledge on whether country or industry factors could affect the study findings. When the sample is restricted to a single industry, on the other hand, it is possible to implicitly control confounding factors that potentially produce higher internal validity. A multi-industry sampling frame is defined under multi-industry studies (Ittner et al., 2003). Secondly, the interpretative viability is perceived differentially by firms with regard to the balanced scorecard (Benders & van Veen, 2001). Management concepts are in intangible in nature and could open up a space where suppliers and users can shape use and content. Consequently, there are challenges related to empirical measurements and definition of concepts as well as their incidences. The study has stayed clear of the potential problems regarding the empirical investigation of the balanced scorecard. However, the key issues relate to the appropriateness of validity of using Kaplan and Norton’s publications and the measurement of compatibility. Again, identifying the beliefs and values of the BSC in the Swedish context as well as taking preferential treatment of BSC over other candidate MAIs to study came as another limitation. Yet, the study has provided elaborate explanations on how to address these issues and present tests relating to the significance of the potential problems. The results do not capture the complexity of real-life situations despite the tests being non-significant and simple. Thirdly, the sample of the study had only one respondent per firm where each individual responded to questionnaire, and who were knowledgeable on the issues the study covered. With multiple respondents per firm, would perhaps have resulted in more reliable data. Fourth, the study relies on retrospective recall of events. With the passage of time, it could be more difficult for respondents to accurately recall when and under what circumstances the BSC was adopted. Fifth, the study includes self-reported questionnaire data. Dillman (2000) followed the questionnaire strategy to limit the potential effects of this approach. Finally, possible unstable measures of variables arise from the use of retrospective cross-sectional research methodology which raises methodological concerns. As highlighted earlier, organizational culture remains relatively stable over time. If a candidate innovation were to change, then compatibility could change given its characteristics. The characteristics of the BSC have changed over time as reported by several researchers (Speckbacher et al., 2003). With the change over time of such characteristics, the changes may likely become compatible with organizational culture and influence former non-adopters to adopt. Ax and Greve (2017) examined the possibility of such an effect by conducted two tests. First, the study examined the differences of three types of BSCs by grouping compatible adopters that correspond to the values and beliefs dimensions of the study as developed by Speckbacher et al. (2003). With only one exception, the study found no such differences since the Type 3 BSC adopters are the most sophisticated type and focus more intently on intuition-based decision-making compared to types 1 and 2 BSCs adopters. Second, compatible BSC adopters within the same group compared to the previous test are examined at different stages of the diffusion cycle. The first is type 1, followed by type 2 and type 3 in that order. As new types of BSCs are introduced, the characteristics of the BSC change over time. The study expects to find a positive relationship between the adoption period and BSC type because BSC is compatible with organizational culture. However, no such relationship was found despite firms adopting later in order to favor more sophisticated BSCs. The two test results showed little evidence because the characteristics of the BSC change over time and compatibility may have changed meaning that it is impossible to completely rule out the possibility affecting the study. As the study relies entirely on the typology of BSCs as provided by Speckbacher et al. (2003), it confirms the limitation of the tests. Remotely, there could be firms in the study that may have adopted other BSC types with other characteristics such as rhetorical elements and packages of design characteristics (Ax & Bjørnenak, 2005). In fact, the research method used may not be qualified as compatible with the BSC as compared to the types of the typology that fit with cultural configurations. When such cases exist in this study, it limits the strength of the statistical analysis. As well, the intensity of the competition and the perceived gains of an innovation may change over time. For example, adoption itself could have affected the perceived gains of an innovation with regard to the perceived gains. Attitudes become more negative or positive when firms learn more about innovation. The difference between the two groups will increase if incompatible and compatible adopters react differently. There is a possible result in a significant interaction effect because incompatible firms are more negative as compatible firms become more positive. Similarly, the intensity of the competition could lower the level of the perceived intensity because change has an effect of adoption. Meanwhile, innovation implementation has a possibility of increasing the compatibility of adopters. Areas of improvement can be; Areas of improvement in MAIs should showcase more findings on further research. This study illustrated previously been suggested that it is more difficult to understand the drivers of adoption in the early phases of the diffusion process. Although it looks more complex, improvement can be made on the innovation assessment process and the motivations of early adopters by analyzing innovations in all critical phases of diffusion. 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