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This study examines the effect of crucial factors (benefits and sacrifices) influencing employees' perceived values (hedonic and utilitarian) towards metaverse meeting platforms. Further, the study investigates the impact of employees' perceived values (hedonic and utilitarian values) on behavioral intention to use metaverse meeting platforms. The study also examines how behavioral intention to use metaverse meeting platforms influences organizational SDG achievement. Finally, the authors analyzed the moderating impact of employee creativity.

Data were collected from 228 participants through structured questionnaires, and the hypotheses were examined using the structural equation modeling approach.

Social presence and technostress are significantly associated with perceived hedonic value. Further, social presence, exhaustion and technostress are significantly associated with perceived utilitarian value. Similarly, perceived hedonic and utilitarian value is significantly associated with behavioral intention to use metaverse meeting platforms. Further, behavioral intention to use metaverse meeting platforms is also significantly associated with SDG achievement.

The study enriches the existing literature pertaining to the metaverse, strategic human resources, sustainability, employee creativity and technology adoption. The research also enriches the value-based adoption (VAM) and stimulus-organism-response (SOR) theories.

Participants will learn to analyze the basis of consumer segmentation in management education. It will specifically highlight the importance of positioning in influencing the marketing strategy of a firm and discuss the importance of a differentiated-low cost strategy to gain competitive advantage. The case will familiarize students with the business environment of rural India, and the applicability of the 4A’s and the 5D’s framework. Finally, the case will help participants understand the difference between a rural market and a Bottom-of-Pyramid (BoP) market.

A rural MBA institute for BoP students is grappling with the problem of low admissions, leading to an existential crisis. Two divergent options are presented to the protagonist. The first is to close down the B-school and use the infrastructure and facilities for a well-funded government skill development program which is vocational and intended for creating blue-collar workers. The second is to find ways to bolster the B-school to ensure that it gets adequate student enrollment, thereby leading to profitability.

This case is suitable for an undergraduate or MBA course in marketing management, rural marketing in India, South-Asian marketing or strategic marketing.

Teaching notes are available for educators only. Please contact your library to gain login details or e-mail support@emeraldinsight.com to request teaching notes. There is an accompanying spreadsheet with the case for studying the market. It contains relevant market data that would support analysis of the case. Comments are added for easy understanding. Instructors can access the separate spreadsheet that works out the break-even calculations for the fee structure of the institute. Instructions on calculations as well as comments are added for easy understanding.

CSS 8: Marketing.

Knowledge sharing (KS) helps employees learn from errors, but not much research has highlighted how sharing practices develop and take place in networked organizations. This study aims to explore how the professionals in a service triad develop and execute KS practices to learn from error.

A case study approach was adopted that focused on professionals working in a US-based company that was part of a health insurance service triad. The organization (“CaseCo”) processed the insurance claims filed by hospitals and doctors. The authors gathered qualitative data by conducting nine focus group discussions (FGDs) among CaseCo’s professionals. The FGDs involved a total of 51 professionals (17 women and 34 men) working in three centres of CaseCo in India.

The analyses revealed that error-related knowledge sharing (ERKS) practices emerge in a professional service triad (PST) through a culture of situated learning. They occur in ways that involves the use of repositories on the one hand, and connections between individuals on the other, both within and across the PST’s organizations. Such practices represent a dynamic system of knowledge stocks and flows in the PST.

To the best of authors’ knowledge, this is the first study that brings to the fore how ERKS practices develop and are executed in a professional organization in a triadic network structure.

The purpose of this paper is to identify potential constraints and determine the constraint structure in a steel manufacturing plant. “Potential constraint” is defined as a factor that is either a constraint at present or can become one in the future and “constraint structure” is used to denote the network of influences between the potential constraints in an organization.

A three-step methodology was followed. First, potential constraints in a steel manufacturing plant were identified with a literature review and expert inputs. Then, the fuzzy decision-making trial and evaluation laboratory (fuzzy DEMATEL) technique was applied to uncover the structure and finally, an ex-post validation and refinement of the results was done with help from other experts.

A total of 10 key potential constraints to steel manufacturing were identified. The two outputs of fuzzy DEMATEL – the influence scatter plot (ISP) and the influence network diagram (IND) – together reveal the constraint structure. The 10 potential constraints could be classified into three types – influencers, mediators and influenced – respectively. Of these “Top management commitment (TMC)” and “Clear vision and long-term planning (CLP)” influence other factors the most, and are themselves influenced the least; while “Customer Relationship Management (CRM)” is most influenced by other factors, while influencing other factors the least.

Potential constraints and the constraint structure can help decision makers in a steel manufacturing plant to identify which organizational factors to address and achieving the plant's goals.

This is the first study that analyzed organizational level constraints in a steel manufacturing context.

Previous research has investigated knowledge transfer and the external consultant's role in it, during enterprise resource planning (ERP) implementation. In this study, the authors explore the processes through which knowledge creation happens during ERP implementation and how external consultants help operationalize the same.

The authors engaged the SECI model of the theory of organizational knowledge creation and conducted an interpretive study that interviewed 14 ERP implementation experts in India. The interviews were transcribed and then analyzed using the ATLAS.ti package.

The findings reveal fine insights into how knowledge creation takes place during ERP implementation through the four modes of knowledge conversion – socialization (S), externalization (E), combination (C) and internalization (I). The external consultants aid in operationalizing this knowledge creation process through five types of knowledge-related activities: (I) importing external knowledge, (D) discovering internal knowledge, (E) extricating confined knowledge, (A) activating flows of knowledge and (S) solving problems using knowledge. These activities can be represented by the acronym, I-D-E-A-S.

The study makes two overarching contributions: (1) offering an interpretation and description of ERP implementation as a knowledge creation process and (2) extending the understanding of the external consultants' role during ERP implementation to include new knowledge creation.

Effective human resource management and organisational success depend heavily on measuring employee performance. This paper aims to investigate multiple factors that are crucial in assessing and measuring employee performance in Indian manufacturing sectors. Further prioritisation of the manufacturing industries based on their practices is conducted to measure employee performance.

The LOCOW approach has been used in this study to determine the relative weightage of the factors that assist in measuring employee performance, and the MARCOS method prioritises manufacturing industries.

Through weightage, criteria show that task performance is given the most weightage, followed by adaptability and contextual performance in the manufacturing sectors. The top three industries are oil and gas, steel and automobile.

This study gives manufacturing industries the tools they need to improve their HR practices, get better work from their employees and stay ahead of the competition in a constantly changing industry.

The current work examines the weightage among the factors that aid in assessing employee performance; further, the use of MARCOS technique prioritises the industries, which can be considered the original contribution.

This research investigates the capabilities of Cloud-based Building Information Modelling (CBIM) in managing quality asset information, drawing upon software engineers' perspectives. Compelling statistics highlight the relationship between building information and environmental sustainability. However, despite the growing utilisation of CBIM in the Architecture, Engineering and Construction (AEC) industry, a significant knowledge gap remains concerning its effectiveness in maintaining quality asset information.

This study employed an exploratory qualitative approach, utilising semi-structured interviews with thirteen software engineers actively developing technological solutions for the AEC industry. Following thematic analysis, the findings are categorised into four dimensions: strengths, weaknesses, opportunities and technological limitations. Subsequently, these findings are analysed in relation to previously identified information quality problems.

This research reveals that while CBIM improves project coordination and information accessibility, its effectiveness is challenged by the need for manual updates, vulnerability to human errors and dependency on network services. Technological limitations, notably the absence of automated updates for as-built drawings and the risk of data loss during file conversions in the design phase, coupled with its reduced capability to validate context-specific information from the user's viewpoint, emphasise the urgent need for managerial strategies to maximise CBIM's capabilities in addressing information quality problems.

This study augments the understanding of CBIM, highlighting the managerial implications of a robust information management process to safeguard information integrity. This approach fosters sustainable practices anchored in reliable information essential for achieving desired outcomes. The findings also have broader managerial implications, especially for sectors that employ CBIM as an instrumental tool.

The purpose of this study is to examine how the adoption of blockchain technology can improve organizational sustainability and what are the contributions of morality, ethics and governance in this scenario.

This study has used different literature and theories to build a successful theoretical model and then validated it using the partial least squares structural equation modeling approach. Various statistical modeling analyses have been performed to test the robustness of the proposed model, which is found to be effective and unique as it has a high explanatory power.

This study has found that adoption of blockchain technology can improve the sustainability performance of organizations. It has also highlighted that organizational sustainability will be further enhanced if the underlying algorithms of blockchain technology are transparent to make the applications moral and ethical. This study has further demonstrated that appropriate governance of blockchain technology can support the organizations to enhance their sustainability performance.

This study demonstrates the importance of an organization’s governance over blockchain technology and its impact on sustainability. The study provides valuable input to practitioners and policy makers regarding blockchain technology and its governance models. Also, the study provides valuable recommendations to leaders and managers of organizations on how to successfully adopt blockchain technology.

This study presents a unique theoretical model to explain the influence of the adoption of blockchain technology and an organization’s sustainability. The study also adds value to the overall body of literature in the areas of ethics, governance and blockchain technology along with sustainability.

This research investigates the distinct characteristics of blockchain technology to safeguard against the deterioration of handover information quality in the post-construction phase. The significance of effective management of handover information is highlighted by global building failures, such as the Grenfell Tower fire in London, UK. Despite existing technological interventions, there remains a paucity of understanding regarding the factors contributing to the decline in the quality of handover information during the post-construction phase.

This study employed a multi-case studies approach across five higher education institutions. It involved conducting semi-structured interviews with 52 asset management professionals, uncovering the underlying reasons for the decline in handover information quality. Building on these insights, the study performed a mapping exercise to align these identified factors with blockchain technology features and information quality dimensions, aiming to evaluate blockchain’s potential in managing quality handover information.

The study findings suggest that blockchain technology offers advantages but has limitations in addressing all the identified quality issues of managing handover information. Due to the lack of an automated process and file-based information exchange, updating handover information still requires an error-prone manual process, leading to potential information loss. Additionally, no solutions are available for encoding drawings for updates and validation.

This study proposes a framework integrating blockchain to enhance the information management process and improve handover information quality.

Visual inspection and human judgement form the cornerstone of daily operations and maintenance (O&M) services activities carried out by facility managers nowadays. Recent advances in technologies such as building information modelling (BIM), distributed sensor networks, augmented reality (AR) technologies and digital twins present an immense opportunity to radically improve the way daily O&M is conducted. This paper aims to describe the development of an AR-supported automated environmental anomaly detection and fault isolation method to assist facility managers in addressing problems that affect building occupants’ thermal comfort.

The developed system focusses on the detection of environmental anomalies related to the thermal comfort of occupants within a building. The performance of three anomaly detection algorithms in terms of their ability to detect indoor temperature anomalies is compared. Based on the fault tree analysis (FTA), a decision-making tree is developed to assist facility management (FM) professionals in identifying corresponding failed assets according to the detected anomalous symptoms. The AR system facilitates easy maintenance by highlighting the failed assets hidden behind walls/ceilings on site to the maintenance personnel. The system can thus provide enhanced support to facility managers in their daily O&M activities such as inspection, recording, communication and verification.

Taking the indoor temperature inspection as an example, the case study demonstrates that the O&M management process can be improved using the proposed AR-enhanced inspection system. Comparative analysis of different anomaly detection algorithms reveals that the binary segmentation-based change point detection is effective and efficient in identifying temperature anomalies. The decision-making tree supported by FTA helps formalise the linkage between temperature issues and the corresponding failed assets. Finally, the AR-based model enhanced the maintenance process by visualising and highlighting the hidden failed assets to the maintenance personnel on site.

The originality lies in bringing together the advances in augmented reality, digital twins and data-driven decision-making to support the daily O&M management activities. In particular, the paper presents a novel binary segmentation-based change point detection for identifying temperature anomalous symptoms, a decision-making tree for matching the symptoms to the failed assets, and an AR system for visualising those assets with related information.