Using interpretive structural modelling to identify and rank performance measures

Modelling and classification of barriers in the construction of smart villages in developing countries

Smart Villages are an innovative solution for tackling global sustainability per the sustainable development goals set by the United Nations. This particular study looks into the implementation of a similar Smart Village concept in developing countries such as Pakistan. The main focus is to identify and classify a set of barriers that are to be considered while constructing a smart village. The hierarchal modeling of these barriers is carried out using Interpretive Structural Modelling (ISM) and then classified into clusters or segments using a Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) technique. Fourteen barriers are selected from the literature and their pair-wise relationships are determined using input from experts, gathered via a questionnaire. The structural self-interactive matrix and reachability matrix were constructed using survey results and binary quantification. Conclusively, deforestation was determined to be the strongest driving barrier alongside crime rate, unemployment, and public rejection while market disruption was the most dependent barrier. The MICMAC analysis was then used to cluster the barriers into 4 categories, based on their dependence and driving power parameters. The study can be useful for the Governments of developing countries especially in South Asia, in prioritizing key elements before constructing a smart village to prevent further damage down the line. The ISM technique has proven to be a valuable resource in organizing data for novel problems with little available data. Since there are only a handful of Smart Village examples to go by, no key data is available previously for this topic. Therefore, this research bridges the gap and provides valuable qualitative and quantitative data to the concerned authorities.

Analysis of barriers to photovoltaic waste management to achieve net-zero goal of Canada

Photovoltaic (PV) installations are experiencing a worldwide exponential upsurge, and the subsequent PV waste is a growing concern. This study identifies and analyzes the critical barriers to PV waste management to achieve the net-zero goal of Canada. The barriers are pinpointed through a literature review and examined by formulating a framework integrating three methods: rough analytical hierarchy process, decision-making trial and evaluation laboratory, and interpretive structural modeling. The findings show that the barriers have complex causal interrelationships with the irregular generation of PV waste and waste collection center as the two crucial barriers with the highest driving powers and causal effects on others. The anticipated outcome of this research is to assist relevant government organizations and managers in assessing the connections between obstacles related to photovoltaic (PV) waste management, with the aim of developing a viable net-zero strategy for Canada.

Establishing a Green, Lean and Six Sigma implementation model for sustainable construction industry: an analysis of driving forces through ISM-MICMAC approach

Green Lean Six Sigma adoption (GLSA) is an emerging concept that enhances product quality, safety and the overall performance of the firms. Few studies attempted to explore and examine the DFs of GLSA towards creating a strong urge in the stakeholders for long-term economic, ecological and productivity advantages. Major 32 DFs were initially explored to fill this gap by conducting a literature review and semi-structured interviews with different experts. Then, using the Delphi method, 28 DFs pertinent to the construction industry of Pakistan were screened, and established a seven-stages structural model by employing the interpretive structural modeling (ISM) technique. Through Matriced' Impacts Croise's Multiplication Appliquee a UN Classement (MICMAC) method, the DFs were categorized into "autonomous," "dependent," and "linking" segments. The results signify that "energy efficiency," "government incentives," "waste minimization," "resources conservation and recycling," and "water efficiency" were the top five DFs for GLSA. Further, the comparison with other countries reveals that the most significant driving force, "government incentives," is substantial for GLSA in the emerging economy of Pakistan. This article enhances knowledge of significant DFs for GLSA, furnishing a considerable source for managers, professionals, and policymakers to encourage GLSA at a wider level.

Analyzing the determinants of sustainability of China Pakistan Economic Corridor (CPEC) projects: an interpretive structural modelling (ISM) approach

China Pakistan Economic Corridor (CPEC) is a game changer initiative of South Asian Pacific Rim. It has great importance for almost all Asian countries. Its success is expected to dictate the economic development of the stakeholders. The aim of this study is to evaluate the essential determinants deriving the sustainability of CPEC projects. The design of the study comprises of the review of literature, data collection, and analysis. Population under study is the folk of stakeholders of CPEC. Sampling envisages on purposive sampling design, i.e., 14 experts from within the stakeholders. Primary data is collected in the field setting through a survey questionnaire appropriate for the study. ISM is used for modelling and MICMAC for analysis and classification using inductive approach. The findings of the literature survey show that there are 23 prime determinants of sustainability of CPEC projects. The results of ISM show that 13 determinants are at Level-I, nine at Level-II, and one determinant namely "economic globalization" is at Level-III being the most critical and driving determinant. The findings of MICMAC show that only one determinant is classified in independent quadrant, and all the remaining determinants are in linkage quadrant, whereas, no determinant is shown in autonomous and/or dependence quadrant. But most of the determinants have potential to be classified in dependent and independent quadrants. It is intimately evident that the results of MICMAC corroborate the results of ISM. It is useful for folk of the stakeholders by way of developing an understanding about the multitude of determinants, intra-determinant relations, prioritizing the determinants for policy decisions, and/or for building future studies. This study has some limitations, e.g., the study uses qualitative approach and answers what and how questions that do not quantify the relations or tell the cause of indicated relations.

The mediating role of knowledge management processes in the effective use of artificial intelligence in manufacturing firms

Purpose

This paper aims to provide and empirically test a conceptual model in which artificial intelligence (AI), knowledge management processes (KMPs) and supply chain resilience (SCR) are simultaneously considered in terms of their reciprocal relationships and impact on manufacturing firm performance (MFP).

Design/methodology/approach

In the study, six hypotheses have been developed and tested through an empirical survey administered to 120 senior executives of Italian manufacturing firms. The data analysis has been carried out via the partial least squares structural equation modelling approach, using the Advanced Analysis for Composites 2.0 variance-based software program.

Findings

Using a conceptual model validated using an empirical survey, the study sheds light on the relationships between AI, KMPs and SCR, as well as their impacts on MFP. In particular, the authors show the positive effects of the adoption of AI on KMPs, as well as the influence of KMPs on SCR and MFP. Finally, the authors demonstrate that KMPs act as a mediator through which AI affects SCR and MFP.

Practical implications

This study highlights the critical role of KMPs for manufacturing firms that can deploy AI to stimulate KMPs and through attaining a high level of the latter might succeed in enhancing both their SCR and MFP.

Originality/value

This study demonstrates that manufacturing firms interested in properly applying AI to ameliorate their performance and resilience must carefully consider KMPs as a mediator mechanism.

Understanding the interaction among enablers of quality enhancement of higher business education in Pakistan

This study aims to generate a list of enablers of quality enhancement of higher business education in Pakistan and build a structural model of enablers to prioritize them. It also intends to impose direction and hierarchy on the inter-relationships of the enablers. The study's design consists of a literature review, data collection from primary sources, and qualitative analysis. Interpretive Structural Modeling (ISM) coupled with Matriced' Impacts Cruise's Multiplication Appliquée a UN Classement (MICMAC) is used as a research methodology. The classical procedure of ISM and MICMAC is applied to primary data collected by a field survey from a panel of experts recruited from folks of stakeholders of business education. Results of the literature show that eighteen critical enablers enhance the quality of higher business education in Pakistan. Results of ISM show that the enabler 'job placement of graduates' occupies the top-level of the ISM model being least critical. In contrast, the enabler 'intra-academia linkages' occupying the bottom of the model is the most vital. Results of MICMAC show that all enablers, except 'job placement of graduates, are classified into linkage clusters, whereas 'job placement of graduates' is classified as an independent cluster. Overall results of the study show that enablers of quality enhancement of higher business education in Pakistan are agile and not settled. The study has profound theoretical, managerial, and practical implications for all stakeholders of business education. It also provides a research framework for future studies concerning subject phenomena. The discussion about the structural model culminates into policy guidelines for the regulators. The study is subject to some methodological/data/resources limitations like the limited review of literature, collection of data from a medium-size panel of experts from Pakistan only, using majority rule for aggregating responses, answering only that what is related to what, other common limitations of qualitative studies, shot period and absence of financial support. The authors conduct this study in a real-life field setting is built on the original dataset and address the efficient issue of phenomenon understudy differently. It is theory-building research, therefore, does not require prior theory. It exploits simple elementary concepts of Boolean algebra, set theory, and graph theory that generates new in-depth information for stakeholders.

Modeling critical success factors for sustainable LSS implementation in hospitals: an empirical study

Purpose

The objective of this paper is to investigate, assess and develop a hierarchical model to evaluate the interrelationship of critical success factors (CSFs) that influence the deployment of Sustainable LSS framework in hospitals. Further, developed model has been validated to investigate its applicability in hospitals towards sustainable LSS implementation.

Design/methodology/approach

“Interpretive Structural Modeling” (ISM) has been utilized to develop a convenient hierarchy and contextual relationship of key CSFs throughout the implementation pathway in Indian healthcare industry through systematic literature review and expert opinion, which is ensured by a taxonomy of CSFs using MICMAC (“Matrice d' Impacts Croisés-Multiplication Appliquée á un Classement”) and questionnaire-based survey to empirically validate the model through utilizing “Structural Equation Modelling” (SEM).

Findings

In this study, 17 keys CSFs to sustainable LSS implementation in healthcare industry have been investigated, and modeled. “Social and environmental responsibility,” “Financial return and project success stories,” “Top management involvement and leadership to implement Sustainable LSS,” “Availability of required resources, and their efficient utilization” are found to be the most essential CSFs for successful sustainable LSS implementation in healthcare industry. Further, classification of CSFs has been done for better interpretation of their nature using MICMAC approach. Moreover, the applicability of the proposed model has been empirically assessed utilizing SEM.

Research limitations/implications

The scrutiny of data reveals that the initial inputs from experts throughout the ISM pathway could trigger biased inputs into the study and generalization of the results into others, it might be viable that this propounded model might trigger distinct outcomes for contrasting types of healthcare organizations.

Practical implications

This model on sustainable LSS would support the decision-makers, practitioners and researchers to predict key CSFs through deployment and support the existing academic research on sustainable LSS. Accordingly, the focus on the CSFs of the sustainable LSS can be prioritized to diminish waste, and enhance patient satisfaction and safety.

Originality/value

This paper is an original contribution of analysis of CSFs in Indian healthcare industry utilizing an integrated ISM-MICMAC and SEM approach.

Prioritization and ranking of lean practices: a case study

Purpose

The paper aims to identify, prioritize and rank lean practices in the context of an Indian automotive component manufacturing organization using interpretive ranking process (IRP) and interpretive structural modeling (ISM) approaches.

Design/methodology/approach

Lean practices are identified from the literature. Then, two hierarchical models were are developed using two distinct modeling approaches – ISM and IRP with expert opinions from an Indian automotive component manufacturing organization to analyze the contextual relationships among the various lean practices and to prioritize and rank them with respect to performance dimensions.

Findings

In the study, the hierarchical structural models are developed using ISM and IRP approaches for an Indian automotive component manufacturing organization. In ISM-based modeling, lean practices can be categorized into five levels. Top priority should be given to the motivators followed by value chain, system/technology and organization centric practices. IRP model shows the dominance relationship among the various lean practices with respect to performance dimensions.

Practical implications

The models are constructed from the organizational standpoint to evaluate their impact to the implementation of lean manufacturing. The study leverages the organizations to prioritize limited resources as per the hierarchy. Managers get the inter-linkages and ranking of various lean practices, which leads to a better perspective for the effective implementation of lean. The structural models also assist management to assign proper roles to employees/departments for effective lean implementation.

Originality/value

There is hardly any structural model of lean practices in the literature for clustering, prioritizing and ranking of lean practices. The study fills this gap and develops the hierarchical models of lean practices through IRP and ISM approaches for an Indian automotive component manufacturing organization. The results from both approaches are compared for illustrating the benefits of one over the other.

Analyzing the Stressors for Frontline Soldiers Fighting Against Coronavirus Disease 2019 Pandemic

This study aimed to analyze stressors to which medical staff is vulnerable due to the coronavirus disease 2019 (COVID-19) pandemic. It also imposes a hierarchy on complex relations among stressors for excavating underlying structure and builds a model of interrelationships contrasting reality. The design of this study comprises a literature survey, data collection from primary sources, and analysis. Stressors have been explored from within current published/unpublished literature and validated by experts through approval vote. Data were collected from the focus group (panel of experts), and interpretive structural modeling (ISM) was used as the research methodology. Findings of ISM are avowed through "cross-impact matrix multiplication applied to classification" (MICMAC) analysis. As a result of the literature survey, a list of stressors was generated, and a total of 19 stressors qualified as representative of the phenomenon. The results of ISM show that two stressors (i.e., "unavailability of proper personal protective equipment (PPE)" and "lack of proper communication") emerged as the most critical stressors since they occupy the bottom of the model, whereas, four stressors (i.e., "anxious about isolation/quarantine," "subject to violent crimes," "feeling frustrated and powerless," and "exhausting shifts/hours without clear end") are relatively less critical since they occupy the top of the model. The rest of the stressors occupy the middle of the model and therefore, have moderate-severe effects on frontline soldiers. The results of MICMAC show that the stressor "subject to violent crimes" is classified in the dependent cluster and the remaining fall in the linkage cluster but no stressor falls in independent and autonomous. Overall results indicate that all stressors are relevant to the phenomenon under this study, but they are currently not settled. This study is invaluable for policymakers, frontline soldiers, researchers, the international community, and society since it provides a lot of new information that is helpful in refining strategies and combating influential stressors.

Internet of Things adoption barriers in the Indian healthcare supply chain: An ISM-fuzzy MICMAC approach

Internet of things (IoT) plays a significant role in offering a wide range of benefits to the healthcare supply chain. It improves the quality of patient care, reduces the cost of medical procedures, maintaining flawless operations and supports clinical decisions. Despite strong policy interest and vast potential benefits of IoT in the healthcare supply chain, the actual adoption rate is relatively low and it's in the nascent stage in developing countries like India. The objective of this paper is to identify and analyze the potential barriers which would restrain the healthcare industry from adopting IoT. Based on the review of the literature and brainstorming with experts from industry and academia, 14 barriers were identified for IoT adoption. The contextual relationship between the identified barriers was developed using interpretive structural modeling and the obtained results were used as input to fuzzy MICMAC analysis to determine the driving and dependence power of the IoT adoption barriers. From the result, Legal and regulatory standards, Lack of IT Infrastructure are major barriers influencing the adoption of IoT in the healthcare supply chain. The findings will support the decision-makers to understand the contextual relationship between the IoT adoption barriers in the Indian healthcare supply chain.

Analyzing the Underlying Structure of Online Teaching During the COVID-19 Pandemic Period: An Empirical Investigation of Issues of Students

The aim of the study is to reveal the underlying structure of issues of university students taking online classes during the COVID-19 pandemic period. The overall design of the study includes a review of contemporary literature and field survey for data collection and analysis. Discourse of literature coupled with expert opinion has been employed for identification of issues. Interpretive Structural Modeling (ISM) is used for the determination of intra-issue relationships and analyzing the underlying structure. Cross impact matrix multiplication applied to classification (MICMAC analysis) is used as a technique for classifying issues on the basis of driving-dependence power. Results of the literature show that there are 21 major issues faced by the students taking online classes. ISM shows that lack of institutional guidelines, lack of regulators' guidelines, stress of pandemic situation, and abrupt (not planned) start of online classes are the most critical issues. MICMAC analysis reveals that there is no autonomous issue, 4 (i.e., connectivity issue, shy to use technology, lack of institutional guidelines, and stress of pandemic situation) are independent, 6 other issues are dependent, and the remaining 11 are linking. This is a valuable study having practical implications for regulators, students, parents, and society to understand the current problem. It is an original attempt that contributes toward literature in the form of a structural model and a diagram of classification of issues.

An integrated AHP-based scheme for performance measurement in humanitarian supply chains

Purpose

In recent years, several performance indicators have been proposed in humanitarian supply chains (HSCs). Selecting the most relevant key performance indicators (KPIs) is challenging for some humanitarian organizations (HOs) because it involves a considerable amount of complexity and information overload which could lead to judgment biases in the decision-making process. Existing performance measurement studies lack critical analysis for prioritization of performance indicators. Since the process of KPIs selection and categorization is a complex, domain based and subjective process, a systematic guideline is needed. To address this gap, the purpose of this paper is to propose an integrated performance measurement scheme that can consolidate KPIs into an overall performance score based on the weighting of the performance indicators in HSCs.

Design/methodology/approach

Data collection was based on questionnaire surveys and direct interviews with practitioners from international HOs.

Findings

This paper proposes an integrated scheme based on balanced scorecard and analytic hierarchy process for performance evaluation of HOs.

Research limitations/implications

The respondents were limited to the humanitarian logistics experts from Malaysian-based international HOs.

Practical implications

The scheme enables the benchmarking of HOs’ performance that could be useful for decision makers in HSCs.

Originality/value

This paper provides the ranking and prioritization of KPIs in HSCs. The approach presented in this paper enables an effective and integrated performance measurement in HSCs.

Sustainable Supply Chain Management Practices in Petrochemical Industry Using Interpretive Structural Modeling

Across different geographical and industrial boundaries, different firms are attempting to implement sustainability in their supply chain in response to pressures from different groups. This article aims at identifying and analyzing influential practices for implementing sustainable supply chain management (SSCM). By determining these practices, top management can focus on them in order to improve the performance of their supply chains. The petrochemical industry was selected because of its role in the Iranian economy and its considerable environmental and social impacts. The interpretive structural modeling (ISM) technique was used as a useful technique to identify interrelations between different sustainable practices. According to the results, set up reduction and pull production system (related to JIT practices) are driving other practices, and these practices have vital role among other practices. There are four practices related to evaluating and collaborating suppliers and other industry peers, which occupy the highest level.

On evaluation of supply chain’s ecosilient (g-resilient) performance index

Purpose

Recently, in turbulent and highly competitive marketplace, organizational sustainability in the long run necessitates the adaptation of appropriate supply chain (SC) strategies. Hence, traditional SC philosophies are being restructured nowadays to fulfill different business goals. Articulation of lean, agile, green and resilient SC strategies could amply be found in the literature; however, integration of those in various modes may definitely improve overall SC’s performance. Past researchers have focused on the integration of lean, agile and green paradigms together to ensure an efficient SC construct. But the integration of green and resilient paradigm has been rarely reported in the literature. To deal with the unexpected situations/disturbances in the SC management along with embedded environmental consciousness, the purpose of this paper is to integrate the resilient SC and green SC philosophies; thereof to evaluate of an overall SC “g-resilient”/“ecosilient” index for a case automotive company.

Design/methodology/approach

A consolidated list consisting of supply chain practices (combining green and resilient performance indices) have been articulated in this study. A decision-making group has been assumed; where, the role of the decision makers is to provide individuals’ judgment (subjective opinion) toward determining the weight and the rating (performance extent) of various performance indices. The overall g-resilient SC performance has been determined by computing a unique ecosilient (g-resilient) index. The concepts of fuzzy performance importance index along with Degree of Similarity (DOS) adapted from fuzzy set theory (FST) have been applied to rank various performance indicators. In addition to that, the interrelationships amongst various g-resilient indices (performance indicators) have also been established through interpretive structural modeling.

Findings

By exploring the concept of fuzzy DOS, outlined in the trapezoidal fuzzy numbers set theory, various SC performance indicators have been classified into three distinct performance categories/levels (namely regretful, tolerable, and satisfactory). Such categorization has been found helpful in order to determine ill (poor) performing SC areas, which need future improvement toward boosting up the overall g-resilient index of the company’s SC.

Originality/value

The study bears significant managerial implications. The decision support framework suggested in this paper is found capable enough to determine a unique index known as “ecosilient (g-resilient) index” toward exploring “greenness” as well as “resiliency” for the case automotive company. Application potential of the proposed ecosilient (g-resilient) index evaluation system has been explored in this reporting. The recommended framework enables the managers to cope up with unexpected disruptions and found helpful in order to reduce the environmental impacts.

"There is no carnival without samba": Revealing barriers hampering biodiversity-based R&D and eco-design in Brazil

Considering the unique relevance of Brazilian biodiversity, this research aims to investigate the main barriers to biodiversity-based R&D and eco-design development in a leading national company which has been commended for its innovation and sustainability. The methodology for this research was based on on-location visits, in-depth interviews, and consensus building among R&D, sustainability, and quality managers. A multi-criteria decision-making (MCDM) approach was adopted through interpretive structural modelling (ISM), a method that assists decision makers to transform complex models with unclear data into structural models. Some of the most influential barriers to biodiversity-based eco-design initiatives are "lack of legal incentive", "not enough demand from the market", and "not enough available knowledge/scientific data." The most relevant barrier was "no legal incentive" from government. Consequently, managers should concentrate their efforts in tackling those barriers that may affect other barriers known as 'key barriers'. Government should work decisively toward promoting a framework of legal incentives for bio-based eco-design; otherwise, metaphorically, "there is not carnival without the samba singer who pushes the rhythm". The results given here reveal the barriers for bio-based eco-design in a Brazilian leading company, and this is the first work combining ISM to barriers to biodiversity R&D and eco-design.

Building Ambidextrous Supply Chains in SMEs

Ambidexterity involves developing competencies to excel simultaneously on the exploration and exploitation dimensions. Few studies in literature discuss ambidexterity in a supply chain context. The research presented in this paper highlights issues that act as barriers and deserve attention in implementing ambidextrous supply chain strategy in SMEs. To develop a relationship structure existing among these variables, Interpretive Structural Modelling (ISM) technique is used. Further, variables' impact and dependency is calculated using Impact Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) approach. ISM algorithm proves to be a better tool as compared to a large-scale generic questionnaire based study due to its iterative nature that helps to bring forth issues that are difficult to identify otherwise. SMEs in India under tremendous pressure to excel on exploration and exploitation dimensions would be the major beneficiaries of this study. The hierarchy based structure and the classification of factors based on their impact and dependence, will enhance the understanding of SMEs mangers/owners to improve supply chain performance by eliminating barriers and thereby implementing ambidextrous strategy across the supply chain.

Modelling factors influencing the adoption of smart-home technologies

Purpose

Smart-home technology (SHT) has been identified by the World Health Organization as a possible solution for assisting older people to maintain their independence and to live safely at home when performing the activities of daily living. This study aims to identify the factors, as well as their inter-relationships, influencing senior citizens to adopt elderly-friendly SHT that supports ageing-in-place in high-density Hong Kong living settings.

Design/methodology/approach

An interpretive structural modelling approach has been used to analyse the factors to develop a better understanding of the relationships between factors influencing SHT adoption, and “Matrice d’Impacts Croisés-Multiplication Appliquée à un Classement” analysis has been used to classify the analysed factors.

Findings

The results suggested that strong government support, efficient backup supporting service and the design of user interface devices have been found as the driving factors encouraging the adoption of SHT. Other factors, including the maintenance of devices, levels of usage and penetration of devices, individual needs and financial considerations, were considered as autonomous factors and are less important to the decision to adopt SHT.

Originality/value

This study provides useful information to policymakers and building designers on the human perspective of SHT adoption, such as the needs and requirements of older people to be considered in SHT technical design and appropriate technological solutions.

Propagation of risks and their impact on performance in fresh food retail

Purpose

– The purpose of this paper is to carry out structural analysis of potential supply chain risks and performance measures in fresh food retail by applying interpretive structural modeling (ISM).

Design/methodology/approach

– Inputs were taken from industry experts in identifying and understanding interdependencies among food retail supply chain risks on different levels (sourcing and logistics outside the retail stores; storage and customer interface at the stores). Interdependencies among risks and their impact on performance measures are structured into a hierarchy in order to derive subsystems of interdependent elements to derive useful insights for theory and practice.

Findings

– Using the ISM approach the risks and performance measures were clustered according to their driving power and dependence power. Change in/inadequate government regulations’ are at the bottom level of the hierarchy implying highest driving power and require higher attention and focussed mitigation strategies. Risks like lack of traceability, transport delays/breakdowns and temperature abuse, cross-contamination in transport and storage have medium driver and dependence powers.

Research limitations/implications

– The approach is focussed on food retail supply chains in the Indian context and thereby limits the ability to generalize the findings. The academics and experts were selected on convenience and availability.

Practical implications

– It gives managers a better understanding of the risks and performance measures that have most influence on others (driving performance measures) and those measures which are most influenced by others (dependent performance measures) in fresh food retail and also a tool to prioritize them. This kind of information is strategic for managers who can use it to identify which performance measures they should concentrate on managing the trade-offs between measures. The findings and the applicability for practical use have been validated by both experts and practicing managers in food retail supply chains.

Originality/value

– The work is perhaps the first to link supply chain risks with performance and explains the propagation of risks in food retail supply chains. It contributes to theory by addressing a few research gaps and provides relevant managerial insights for practitioners.

An analysis of the barriers to the proliferation of M-commerce in Qatar

Purpose

– The purpose of this paper is to identify and develop a hierarchical model for the barriers affecting the growth of mobile commerce (M-commerce). Based on the model developed, the authors’ objective is to identify those variables that are of strategic nature and are the root cause of the issue.

Design/methodology/approach

– Variables considered as barriers are identified, and utilizing the interpretive structural model approach, a relationship model is developed. Further, the impact matrix cross-reference multiplication applied to a classification approach is used to analyze the effect and dependence among these factors.

Findings

– The research in the area of M-commerce in the Arab world and related to the strategic aspect is limited in the extant literature. The present study tries to fill this gap by investigating the variables that inhibit the growth of M-commerce in Qatar. The research shows that there exists a group of barriers having a high driving power and low dependence requiring maximum attention and of strategic importance, while another group consists of those variables that have high dependence and are the resultant actions.

Practical implications

– There is a growing concern that although the numbers of mobile subscribers are increasing at a very fast pace in Qatar, actual M-commerce activities in the country remain low. The findings of this study can be used to understand the differences between the independent and dependent variables and their mutual relationships. The study would also help the policy makers to develop suitable strategies to facilitate growth of M-commerce in the country.

Originality/value

– This research was the first attempt to investigate the relationships among the variables inhibiting the growth of M-commerce in a fast-growing economy in a Gulf Cooperation Council (GCC) region. Given that there is limited research on M-commerce in the GCC context, the study can be viewed as an investigation that provides a good understanding of the variables and their interrelationships affecting M-commerce proliferation.

Barriers to implementation of IT in educational institutions

Purpose

– The purpose of this paper is to identify the most significant barriers to successful implementation of information technology (IT) in higher educational institutions (HEIs) of India. Although, educational institutions are investing in IT, they have been not been able to leverage it the same way as other business organizations. The present investigation will assist the management of HEIs to distinguish the key barriers affecting productive IT implementations and further take appropriate measures to deal with it.

Design/methodology/approach

– For the purpose of the study, focus group and semi-structured interviews were conducted with academicians, administrators, functional heads, and IT staff from various HEIs of India. This research attempts to discover the major barriers to successful implementation of IT in HEIs using an interpretive structural modeling (ISM) methodology. Furthermore, structural analysis and classification of barriers is done using MICMAC analysis.

Findings

– The results identified the key barriers that if dealt with can help overcome or lower the effect of other barriers preventing successful IT implementation in HEIs. It will provide roadmap to managers and administrators of HEIs to take appropriate measures to overcome the major barrier to effective implementation of IT.

Originality/value

– Several authors have been studied barriers to implementation of IT in industry and educational institutions, but none have found the most significant barriers that affect successful implementation of IT and may drive other impediments. This research draws inspiration and is being carried out for Indian HEIs.