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This paper aims to highlight the importance of the study of emotions in the successful implementation of information systems projects in developing countries. This paper studies one emotion, namely, anger, and discusses its detrimental impact on information system interventions. This paper suggests that controls are necessary for the management of anger emotion.

This research study explores the case of an Indian agricultural marketing board that implemented an information systems project on the integration of agricultural markets. The data was collected through semistructured interviews from four stakeholder groups. This paper uses a qualitative approach and analyzes the data using thematic analysis. Pierre Bourdieu’s theory of practice is used to study emotions in the case.

This paper finds that anger is the prominent emotion displayed at public sector organizations in India. This paper permeates all aspects of public organizations and has a detrimental impact on successfully implementing the information systems projects. Successful implementation of the information systems (IS) projects in India will need to have a framework for managing the anger emotion.

To the best of the authors’ knowledge, this is the first paper within the information systems discipline that focuses on anger and its detrimental impact on successful IS interventions. A unique contribution of this paper is a framework for the study of emotions. This paper also introduces the idea of controls for emotional management.

The purpose of this study is to understand the trust formation expectations of stakeholders in the implementation of information and communications technology for development (ICT4D) projects.

This paper uses a qualitative methodology inspired by a critical approach. It uses a thematic analysis approach, and draws the results using a constant comparison method. It is guided by the Pierre Bourdieu’s theory of practices. This is an empirical study that uses semi-structured interviews for the data collection.

Lack of an integrated view of emancipatory expectations has a negative impact on the trust levels of stakeholders. An integrated view of emancipation has physical, moral and social dimensions.

The study brings forth the concept of entry point activities (EPAs). To the author’s knowledge, this is the first application of this concept in ICT4D research. EPAs can be used to develop trust relationships between the stakeholders of ICT4D projects.

The purpose of this paper is to propose an approach to evaluate “on time” performance for a class of Indian railways (IR). This approach is build-up on the theme of six sigma level computation for continues data. The arrival data obtained from a class of IR called “Rajdhani Express” exhibited a unique characteristic: neither did the data followed a distribution nor could it be transformed to fit into a distribution. In this work, the authors present an approach to evaluate on time performance of IR, given such “unruly” data.

An attempt is made to develop a lucid approach, given an unruly data. Initially, the authors plot a histogram using Scott’s method. Later, the authors use Taguchi’s quality loss function to assign weights to each of the bins in histogram. Weights to each of the bins are assigned based on the predefined rules. Finally, sigma level is computed by using weighted defect per million opportunities (DPMO) approach. In this paper, the authors discuss the proposed algorithm, an illustrative example with an emphasis on a class of IR.

Given the unique characteristic (unruly data) of arrival data of IR, the proposed methodology helps in quantifying it is on time performance. This method extends the conventional DPMO approach of computing the sigma level. The proposed method is validated using various data sets of different distributions. Further, this approach can be generalized and applied to data set of any distribution. Since distribution of the data is not the pre-requisite, the proposed approach can be applied to compare (and benchmark) data sets of different distributions. This methodology, thus, paves path to develop newer approaches in quantifying and benchmarking the sigma levels.

In this manuscript, the authors present a case of Rajdhani Express trains, a class of IR. A practicing manager can use this approach to compare the performance of various classes of railways and benchmark their performance. Such an approach, with suitable modifications (if any) can be applied to evaluate performance in various service industries.

Usually, if the data are unruly, the sigma level is computed by using ad-hoc methods that may provide compromising solutions and/or inaccurate results. The developed methodology proposes a unique approach to quantify sigma level, given such an unruly nature of the data. This approach thus fills the long needed gap in addressing such situations. This approach can be applied in various similar situations. A case of IR is presented.

The purpose of this paper is to benchmarking the governance performance of Indian states.

This paper provides a framework to measure governance performance at the state level. Using the data on 28 key indicators, the authors evaluate Indian states on seven broad dimensions of governance quality covering several aspects of public service delivery, regulatory quality and law and order. The empirical methodology involves the application of multi-criteria decision making techniques in two steps. The authors, first develop suitable weights of the identified dimensions and criteria under each dimension by applying the inputs of an expert-based decision-panel in a best-worst framework. Next, using these weights, the authors evaluate ranking of each state using TOPSIS and PROMETHEE-II methods.

The results indicate wide disparities in the governance performance of Indian states. Based on different indicators, the paper evaluates the rank of all the major Indian states. Results reveal that “Social Service Delivery(S)” is the most influencing dimension for the development of a state. Overall, the authors find Andra Pradesh, NCT of Delhi and Goa to be the leading states in terms of governance quality.

The paper provides policy makers with easy to use operational indicators to analyse the governance performance of Indian states. These would help in better monitoring of these states through competitive goal-setting for continuous improvement.

To the best of the authors’ knowledge, this study is the first formal assessment of governance quality in the Indian states in a multi-criteria framework. To this end, the paper addresses the issue of wide regional disparities in the country. The findings of the paper provide powerful insights to policy makers in setting up appropriate strategies to eliminate these disparities.

The present research study aims to understand the cause-and-effect reasons behind the job-hopping practices followed by Gen Z employees in the industry 5.0 in India. Further, in the tandem of efforts, the research study has examined the direct and indirect relationship among novice behaviour, social alienation and job-hopping in Gen Z in the information technology sector of Industry 5.0 in India.

The 533 Gen Z or millennial employees were chosen from northern India Industry 5.0 following the non-probability purposive sampling technique. The study follows the quantitative research approach, and the data were collected through a survey questionnaire based on standardized measuring instruments. Further, the gathered data were analysed using the structure equation modelling.

The study’s findings confer the significant direct impact of novice behaviour on job-hopping. While measuring the indirect relationship, the partial mediation effect was noticed in the relationship among novice behaviour, social alienation and job-hopping in the Gen Z employees of Industry 5.0 in India.

The present study will be beneficial to the investors to recognize the job-hopping reasons in Industry 5.0. Further, Gen Z employees and academicians will also receive insight into the cause and effect behind job-hopping. Such will minimize the gap between industry and academia and help Gen Z attain stable employment in Industry 5.0.

This study aims to identify the impact of commercial issues (CIs), financial issues (FIs) and corporate affairs (CAs) on operational excellence (OE) of the mining industry.

A purposive sample of size 321 was collected from Indian mining executives with more than ten years of exposure to the mining field. Factors are identified and confirmed with the use of confirmatory factor analysis. The structural equation modeling technique was then applied to understand the unique as well as the complex relationships between FI, CI, CA and OE.

The results indicate that all three issues, CI, FI and CA, have an influence on OE in the Indian mining industry. Among the variables of the issues considered in this study, marketing products and size and quality of products (from CI); scale of economies (from FI); risk management (from CA); and transportation and machine operation (from OE) are the highest influencing variables.

This study has its limitations in sampling, the timing of sample collection and their mode. The samples were collected from only massively deposited large mines.

Business managers of the mining industry will be more vigilant and aware of those indirect variables such as marketing products, size and quality of products, scale of economies and risk management, which can influence OE apart from major influencing variables such as transportation and machine operations and production scheduling.

To the best of the authors’ knowledge, this is the first study in the mining industry to evaluate the impact of these three issues on OE. The originality of this research lies in testing the CI, FI and CA of the mining industry with OE, which is completely new to this field.

The purpose of this paper is to develop a comprehensive framework to identify and classify key medical tourism enablers (MTEs) and to study the direct and indirect effects of each enabler on the growth of medical tourism in India.

In this paper, an integrated approach using interpretive structural modeling (ISM) and Fuzzy Matrice d'Impacts Croisés Multiplication Appliquée á un Classement (FMICMAC) analysis has been developed to identify and classify the key MTEs, typically identified by a comprehensive review of literature and expert opinion. The key enablers are also modeled to find their role and mutual influence.

The key finding of this modeling helps to identify and classify the enablers which may be useful for medical tourism decision makers to employ this model for formulating strategies in order to overcome challenges and to become a preferred medical tourism destination. Integrated model reveals enablers such as medicine insurance coverage, international healthcare collaboration, and efficient information system as dependent enablers. No enabler is found to be autonomous enablers. The important enablers like healthcare infrastructure facilities and global competition are found as the linkage enablers. Research in medicine and pharmaceutical science, medical tourism market, transplantation law, top management commitment, national healthcare policy, competent medical and para-medical staffs are found as the independent enablers. Integrated model also establishes the direct and indirect relationship among various enablers.

The research provides an integrated model using ISM and FMICMAC to identify and classify various key enablers of medical tourism in India. In conventional cross-impact matrix multiplication applied to classification analysis, binary relationship of various enablers is considered. FMICMAC analysis helps to establish possibility of relationship among various enablers so that low-key hidden factors can be identified. The low-key hidden factors may initially exhibit marginal influence but they may show significant influence later on during analysis. The uncertainty and fuzziness of relationship among various enablers can be conveniently handled by FMICMAC and expert opinions can easily be captured. This research will help medical tourism decision makers to select right enablers for the growth of medical tourism in India.

The purpose of this paper is to identify the dimensions of service quality as well as of service loyalty in the context of medical tourism. It seeks to demonstrate the conceptualization of medical tourism service loyalty (MTSL) construct. This research also attempts to examine the effect of service quality dimensions on service loyalty dimensions of medical tourism.

The dimensions of service quality as well as of service loyalty are identified using an exploratory factor analysis. Next, the reliability and validity of the quality factors and loyalty factors are established through confirmatory factor analysis using AMOS 18.0 version. The related hypotheses are tested using structural equation modeling (SEM).

The paper identifies eight-factor construct for medical tourism service quality and three-factor construct for MTSL. It is found that the treatment satisfaction dimension of service quality has positive and significant impact on MTSL. It is also observed that, overall, medical tourism service quality has positive impact on MTSL.

These dimensions of service quality should be viewed as the levers of improving perceived service quality with respect to medical tourism. Examining the service quality dimensions’ impact on customer loyalty for medical tourism sector can offer the industry valuable insights regarding which aspects of the service to focus on in order to improve medical tourist’s satisfaction and loyalty toward the firms.

This paper introduces the concept of service quality and service loyalty in medical tourism sector. In conceptualizing MTSL, the authors propose an integration of behavioral measures, attitudinal measures and cognitive measures. The interrelationship between the service quality construct and medical loyalty construct was established using SEM. This is useful for the healthcare manager to measure the medical tourist’s perceptions of service quality on these dimensions as related to medical tourism performance.

This research paper aims to develop and validate an enhanced business process improvement methodology (EBPIM) by integrating the DMAIC (define, measure, analyze, improve and control) and the comprehensive business process management (CBPM) methodologies.

A systematic literature review and analysis were conducted to prove the novelty of the research approach and identify the similarities, differences, strengths and weaknesses of the DMAIC and the CBPM methodologies. The EBPIM was proposed based on the analysis results. Then, a focus group approach was used to evaluate and validate the methodology.

The EBPIM consists of nine activities: preparation, selection, description, quantification, modeling, enactment, improvement opportunities selection, analysis and improvement and monitoring. The proposed methodology adopted the systematic and structured process of the DMAIC methodology by having one tollgate between every two activities to check the progress and authorize the team to go to the next activity. At the same time, it has the ability of the CBPM methodology to enhance the interaction between human activities and business process management systems (BPMS).

The EBPIM was evaluated and validated by a focus group of academic professors. However, the main limitation of the proposed methodology is that it is still theoretical and needs to be empirically tested. Therefore, future work will focus on testing the EBPIM in different industries and organization sizes.

From the theoretical perspective, the proposed methodology adds value to the knowledge in the scope of business processes improvement methodologies (BPIMs) by integrating the DMAIC and the CBPM methodologies. It takes advantage of and combines the strengths of the DMAIC and CBPM methodologies. From the practical perspective, the proposed methodology presents a valuable tool that can facilitate the organization’s mission to improve the areas that need improvement using a systematic improvement methodology that will effectively enhance organizational performance (OP).

The BPIMs literature analysis proved that most of the reviewed methodologies could not support all phases of the business process improvement (BPI) activities. It was concluded that integrating the DMAIC and the CBPM methodologies is a novel approach. The proposed methodology will enhance the efficiency of both methodologies, fill the gaps that may exist in both of them and lead to better results in terms of BPI.

This paper explores the role of Internet of things (IoT) enabling factors in adopting digital supply chain.

Analytical hierarchy process (AHP) was used to rank performance measures and prioritise the enabling factors. Semi-structured interviews were conducted to validate and support key research findings from the AHP analysis.

The results show that level of customer demand is the most important indicator in adopting IoT while the level of product/process flexibility is the least important. System integration and IoT infrastructure are the top two enabling factors in increasing the level of process stability, supply chain connectivity, and product/process flexibility, respectively. Furthermore, the study suggests that the enabling factors for IoT adoption are directly connected with organisational resources/technological capabilities that support the resource-based view theory. This research identified interdependencies between IoT enabling factors and key performance measures for IoT adoption success in managing the digital supply chain.

Supply chain managers can use the empirical findings of this study to prioritise IoT adoption, based on the relative importance of enabling factors and performance measures. The research findings are focused on broader supply chain practices of large companies rather than a specific industry and SMEs. Hence, any industry-specific adoption factors and SMEs were not evident from this study.

This research study empirically established priorities of enabling factors for IoT adoption, along with inter-dependencies among enabling factors as a basis for developing guidelines for IoT adoption.