Modeling strategic performance management of automobile manufacturing enterprises

Drivers towards Adopting Modular Integrated Construction for Affordable Sustainable Housing: A Total Interpretive Structural Modelling (TISM) Method

This study features the development of a framework to identify drivers towards increasing adoption of modular integrated construction (MiC) methods for affordable sustainable housing (ASH). The rise of offsite construction (OSC) techniques, especially MiC, has been evident in recent years. MiC’s adoption in ASH is still underdeveloped; however, due to various benefits of MiC over conventional construction methods, it is envisioned to be a significant emerging approach for tackling growing housing demand, and ASH in particular. Although a few prior studies identified some factors for utilization of MiC towards ASH, studies to date have not provided a holistic review of drivers or a comprehensive framework of the interrelationships between such drivers. To address this issue, this study utilizes a three-way process including a systematic literature review, semi-structured interviews and the Total Interpretive Structure Modelling (TISM) method to study the drivers for MiC adoption in ASH. Initially, 111 drivers were extracted from a review of 40 studies in the existing literature. Following that, the significant drivers of MiC adoption for ASH were grouped into cost, time, productivity, quality, environmental, social, policy and demand. Drawing on concepts of systems thinking and graph theory, the TISM model for eight drivers was developed from both the literature review and the interview results. Four levels of hierarchy were found among drivers containing linkage, driving, depending and autonomous. Succeeding the steps of TISM and Reachability Matrix (RM) and Matrice d’ Impacts Croises-Multipication Appliqué a Classement (MICMAC) analysis, social drivers were found to have the highest driving and lowest dependency power, followed by productivity and policy drivers. This signifies the importance of social factors for enhancing MiC adoption for ASH. In addition, a strategic framework of boosting MiC adoption in ASH is also presented, highlighting the key stakeholders and strategies for transformation along with conclusions. This study delivers a wider landscape of drivers for MiC-ASH synergy that may assist practitioners, policy makers and relevant stakeholders to better understand the relationships between the drivers.

Cleaner production practices at company level enhance the desire of employees to have a significant positive impact on society through work

Implementation of cleaner production practices (CPP), service quality (SQ) and corporate social responsibility (CSR) is often studied at organizational level. A number of studies on trio have reported it's significant impact on overall organizational performance and profitability across the globe. However, not much is studied about the individual level micro influence of these constructs on employee engagement (EE), organizational pride (OP), organizational identification (OI) and "desire to have a significant impact through work" (DSIW). Therefore, this study presents a comprehensive framework for assessing the impact of the implementation of CPP, SQ and CSR on EE, OP, OI and DSIW. Data collected from 320 non-managerial staff members employed at a garments manufacturing company in Pakistan was analyzed using partial least square (PLS) approach. Findings revealed that the implementation of CPP, SQ and CSR plays an important role in shaping EE, OP, OI and DSIW in the garments manufacturing industry. Further, it is found that the implementation of CPP has a non-significant impact on SQ. Additionally, results of the importance-performance map analysis (IPMA) have also confirmed that the implementation of CPP at company level has shown a highest importance and performance amongst all the latent constructs proposed as predictors of DSIW in the garments manufacturing industry. These findings are a step forward and unique contribution of this study in the domain of CPP, SQ, CSR, EE, OP, OI and DSIW.

Analysis of demand risks for the Indian automotive sector in globally competitive environment

Purpose

The purpose of this study is to understand the different types of risks affecting the demand for the automotive sector in India. The study is further trying to illustrate an approach for analyzing the relative intensities of these risks in the present uncertain business environment.

Design/methodology/approach

Risk on the overall demand is assessed by a combined Bayesian – multi-criteria decision-making approach. Data related to the different factors, affecting their product demand is collected from major automobile firms. Then, weights for these factors are evaluated by applying the analytic hierarchy process approach. Further, these weights are used in the Bayesian analysis network to evaluate the risk intensity for different subgroups, namely, political, economic, social, technological and environmental.

Findings

From the literature and experts’ opinion, total 16 risk factors have been finalized and these are further grouped into 5 categories i.e. political, economic, social, technological and environmental. It is observed that the demand for organizations functioning in the automotive sector is more vulnerable to economic risk as compared to other risks considered in the study.

Practical implications

Managers and decision makers of associated organizations can use the proposed framework to assess the demand risks so as to pre-evaluate their demand corresponding to future changes. Factors can be added or removed and importance could be assigned to different risk factors according to the prevailing business environment for an organization or sector. This will also help the organizations to conduct a more effective risk management in an uncertain business environment.

Originality/value

The study will help in better understanding of the various demand risks prevalent in the Indian auto sector. The methodology used, provides a novel approach for assessing the macroeconomic demand risks and can be used by the firms working in the automotive sector. The proposed methodology could be used for assessing supply chain risk or any other business initiative risk. The suggested approach will help managers in devising flexible management techniques so as to mitigate the risk.

Modified total interpretive structural modelling (TISM) of asymmetric motives and its drivers in Indian bilateral CBJV

Purpose

The purpose of this paper is to examine the elements of asymmetric motives, i.e., initial cross-border joint venture (CBJV) conditions and relative partner characteristics in emerging nations. The two main objectives of the present research are to identify the elements affecting asymmetric motives in Indian bilateral CBJV and to construct modified total interpretive structural modelling (TISM) for the identified elements of asymmetric motives.

Design/methodology/approach

For the current study, the qualitative technique named total interpretive structural modelling was used. The TISM (Sushil, 2012) is a novel extension of interpretive structural modelling (ISM) where ISM helps to understand the “what” and “how” of research (Warfield, 1974) and TISM answers the third question, i.e., “why” in the form of TISM; further checks for the correctness of TISM are given in Sushil (2016). TISM provides a hierarchical model of the elements selected for study and the interpretation of each element by iterative process and also a digraph that systematically depicts the relationship among various elements. TISM is an innovative modelling technique used by researchers in varied fields (Srivastava and Sushil, 2013; Wasuja et al., 2012; Nasim, 2011; Prasad and Suri, 2011). Steps involved in TISM are shown in Figure 1. It uses reachability matrix and partitioning of elements similar to ISM. Also, along with traditional TISM, the modified TISM process was also used where both paired comparisons and transitivity checks were done simultaneously which helped in minimising the redundant comparisons being made in the original process. Furthermore, for identifying the elements of study, SDC Platinum database was used, which was taken from research papers of major journals namely British Journal of Management, Administrative Science Quarterly, Strategic Management Journal, Management Science, Academy of Management Journal and Organization Science (Schilling, 2009). The database included all joint ventures that were formed in India, having India as one of the partner firms during fiscal year April 2000 and March 2010. From these, 361 CBJVs and 76 domestic joint ventures were identified. Although 54 CBJVs were excluded from these, a total number of 307 CBJVs were studied in the current research. Among these 307 CBJVs, 201 were from super-advanced nations (G7), 40 CBJVs from developing nations and 66 CBJVs from other developed nations. As 65 per cent of the CBJVs came from G7 nations (France, Italy, Japan, Canada, Germany, USA and UK), in the current study, we tried to examine Indian CBJVs with G7 partners only for a period of ten years as mentioned above.

Findings

The results of the study indicate that asymmetric motives are directly affected by critical activity alignment and interdependency. Thus, we can conclude that critical activity alignment of partners in CBJV is an antecedent of CBJV motive and thereby minimises the number of asymmetric motives. Bottom level variables such as culture difference and relative capital structure are considered as strong drivers of asymmetric motives. Diversification, resource heterogeneity and inter-partner conflict are middle level elements. Effect of these elements on asymmetric motives can only be improved and enhanced when improvement in bottom level variables is found. It has been believed that as the relative capital structure among firm increases, CBJVs’ asymmetric motives also increase, the reason being that as the difference in capital structure occurs, gradual change in bargaining power will also occur.

Originality/value

TISM used in the present study provides valuable insights into the interrelationship between identified elements through a systematic framework. The methodology of TISM used has its implications for researchers, academicians as well for practitioners. Further study also examines driver-dependent relationship among elements of interest, i.e., relative partner characteristics and initial CBJV conditions by using MICMAC analysis, which can be viewed as a significant step in research related to bilateral CBJV.

Modeling and analysis of FMS performance variables by fuzzy TISM

Purpose

The purpose of this paper is to identify the flexible manufacturing system performance variables and analyze the interactions among these variables. Interpretive structural modeling (ISM) has been reported for this but no study has been done regarding the interaction of its variables. Therefore, fuzzy TISM (total ISM) has been applied to deduce the relationship and interactions between the variables and driving and dependence power of these variables are examined by fuzzy MICMAC.

Design/methodology/approach

Fuzzy TISM and fuzzy MICMAC analysis have been applied to deduce the relationship and interactions among the variables and driving and dependence power of these variables are examined by fuzzy MICMAC.

Findings

In total, 15 variables have been identified from the extensive literature review. The result showed that automation, use of automated material handling, an effect of tool life and rework percentage have high driving power and weak dependence power in the fuzzy TISM model and fuzzy MICMAC analysis. These are also at the lowest level in the hierarchy in the fuzzy TISM model.

Originality/value

Fuzzy TISM model has been suggested for manufacturing industries with fuzzy MICMAC analysis. This proposed approach is a novel attempt to integrate TISM approach with the fuzzy sets. The integration of TISM with fuzzy sets provides flexibility to decision-makers to further understand the level of influences of one criterion over another, which was earlier present only in the form of binary (0, 1) numbers; 0 represents no influence and 1 represents influence.

A validation of the performance management scale

Purpose

The purpose of this paper is to develop a performance management (PM) scale questionnaire that encompasses the pre-requisite, performance planning, performance evaluation, performance review, and performance application dimensions of PM.

Design/methodology/approach

In the study, the 33 questionnaire questions were first validated using exploratory factor analysis (EFA) and then by confirmatory factor analysis (CFA) along the three performance dimensions. The research sample consists of 330 entrepreneurs. The factor analysis results confirm the validity of the questionnaire as a reliable entrepreneur PM evaluation tool, as evidenced by the composite reliability of 0.845 and the average variance extracted of 0.532.

Findings

All constructs revealed the acceptable internal consistency reliability. A good model fit was found for the measurement model using several fit index like χ2=449.983, degree of freedom=415, p-value (p)=0.114, goodness of fit index=0.927, adjusted goodness of fit index=0.901, root mean square error of approximation=0.016, and root of mean square residuals=0.032.

Research limitations/implications

The PM model was examined using EFA and CFA only. A sample with only SMEs entrepreneurs and large sample size and sample area can be used in future research.

Practical implications

This research paper is an endeavor to explore only the reliability and validity of the PM model. Thus all the five dimension, namely “pre-requisite” “performance planning,” “performance evaluation,” “performance review,” and “performance application” proved out of be reliable and validated when it will be tested in case of SMEs’ high-growth sectors and high-impact sectors.

Originality/value

The main contribution of this research is that all factors have a good fit and acceptable reliability value; each factor can be measured individually depending on the nature of the research.

Exploring the status and effects of balanced scorecard adoption in the non-western context

Purpose

The purpose of this paper is to explore the status of corporate performance management (PM) in the Middle Eastern context, represented by the United Arab Emirates (UAE) and the Kingdom of Saudi Arabia (KSA). In addition, the current study investigates the effects of the adoption of the balanced scorecard (BSC) and aims to explore the impact of the BSC on workplace attitudes and behaviors, as shown by accountability, inspiration, and motivation.

Design/methodology/approach

Due to the limited knowledge about the subject matter and the limited number of companies adopting the BSC in the Middle East, this study has adopted a descriptive approach to verify the significance of the BSC and to explore the causal relationship amongst the performance perspectives and the different dimensions of the BSC. The sample was drawn from five major business sectors in the UAE and KSA.

Findings

The results indicate that the BSC indicators are effective tools to evaluate and reflect on corporate performance. The concept of the BSC is considered good practice in the UAE and the KSA. Because of the concept’s compatibility with the local culture and business practices, it can be used to balance shareholder and stakeholder demands.

Research limitations/implications

One of the main limitations of this study is that the sample is drawn from only two countries from the Middle East and, hence, cannot be generalized.

Originality/value

This study is one of the first attempts to explore the status of the corporate PM systems in a non-western context using a BSC technique created and typically applied in the western world. In addition, this study is considered a valuable attempt at exploring the effects of the adoption of this technique on an organization’s performance.

Analysis of Indian retail demand chain using total interpretive modeling

Purpose

The study aims to present demand chain management (DCM) modeling of Indian apparel retailers. This will result in a structured model presenting contextual interrelationship among DCM variables so that retailers can proactively manage their demand chain.

Design/methodology/approach

The research follows an exploratory research design. It initially involves identification and analysis of influential factors of the implementation of DCM practices through the review of literature. Then, these variables were analyzed using total interpretive structural modeling or TISM followed by a statistical verification and case-based validation of the model.

Findings

The major findings of the paper are: top-management commitment and support, information management and supply chain agility in supply chain are the most significant enablers with the highest driving power. The other apparel retail specific significant variables are assortment planning, category management and marketing orientation. The model also indicates that the firms that implement customer-centric DCM practices do well in terms of organizational performance and thereby achieve differential advantage over their competitors.

Research limitations/implications

Because the literature on DCM is still in nascent stage, the study bases itself on interpretive method; that is, TISM of analysis with a limited number of experts. Future studies may consider larger sample with more advanced statistical tools such as structural equation modeling for further validation of the findings.

Originality/value

The novelty of the paper lies in the study of an emerging supply chain philosophy; that is, DCM and its key practices per se. It has rarely been studied from the theory building perspective hitherto. Moreover, TISM-based approach is applied for the first time to study the DCM practices and its drivers vis-à-vis dependents.

Analyzing Lean Six Sigma enablers: a hybrid ISM-fuzzy MICMAC approach

Purpose

The purpose of this paper is to identify Lean Six Sigma enablers (LSSEs) and analyse the interaction among the enablers via a hierarchical model developed by employing interpretive structural modelling (ISM) and determine the driving and dependence power of enablers through fuzzy MICMAC (Matriced’ Impacts Croise´s Multiplication Applique´ea´un Classement) analysis.

Design/methodology/approach

An expert group of industry professionals and academicians is consulted at the initial stage as an input for ISM methodology to explore the paired relationship among LSSEs for each parameter of Lean Six Sigma (LSS) implementation. The outcome of ISM is further utilized by fuzzy MICMAC analysis to discover the enablers that are strong drivers and highly dependent. Fuzzy set is included in MICMAC analysis in order to obtain more precise output and effective model.

Findings

In total, 20 key enablers are identified through a literature review and expert opinion that emerged as the most significant factors towards LSS implementation. The identified enablers are portrayed into a structural form representing as input and output variables. Later, the driving and the dependence power of each enabler is presented in cluster form.

Research limitations/implications

The paired relationships among LSSEs are obtained through the interpretation made by the experts. The judgments of experts are subjective and may be biased; as difference in expert opinion may influence the final outcome. Conducting a large-scale survey may provide a better catch for interactions of LSSEs.

Practical implications

This study provides strong practical implications for researchers as well as industry practitioners. The industry professionals must deliberately focus on the identified LSSEs more conservatively during LSS implementation and the top management should plan strategically to avoid any implementation failure.

Originality/value

The present study identifies 20 crucial enablers of integrated LSS and presents them in a hierarchical form which will be beneficial for researchers and practitioners. The interactions among the enablers shown in cluster form will help in better execution of LSS.