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This study investigates organizations' non-adoption intention towards the enterprise metaverse. The innovation resistance theory (IRT) is used as an underpinning theory to examine the impact of various risks on non-adoption intention towards the enterprise metaverse.

A total of 294 responses were collected to examine the proposed hypotheses. A structural equation modelling technique was used to investigate the hypotheses using SPSS AMOS and PROCESS MACRO.

The results of this study reveal that performance, security and psychological risks are significantly associated with non-adoption intention towards enterprise metaverse. Further, distrust significantly meditates the association between performance risk, social risk, technological dependence risk, security risk and psychological risk and non-adoption intention towards enterprise metaverse. Moreover, the results of moderated-mediation hypotheses indicate that the mediating effect of distrust on the association among performance risk, social risk, psychological risk and non-adoption intention towards enterprise metaverse is higher for individuals having high technostress compared to individuals having low technostress.

The study's findings will enrich the metaverse literature. Further, it provides a deeper understanding of enterprise metaverse adoption from a B2B perspective using the underpinnings of IRT. The study helps organizations understand the risks associated with the adoption of the enterprise metaverse.

Strategic marketing is linked to marketing management. The process is presented by a model, the framework of which can be used for understanding the interrelationships between strategic and practice/implementation considerations within marketing. An attempt is made to synthesise existing knowledge on strategic and practice/implementation linkages with a view to identifying fruitful areas for additional research.

The case will familiarize students to TEARS model and No TEARS approach for brand endorser selection. It will enable the students to understand the extent of influencer impact on the brand. It will make students to realistically assess the pros and cons of ambassador marketing using celebrities. It will also enable the student to devise brand strategies to mitigate the risk associated with ambassador-based marketing.

The case explains the strategic challenge the brand faces in ambassador marketing due to the uncontrollable personal crisis of the celebrity. Brand ambassador is an integral element of the brand persona and is appointed to boost the brand’s unique proposition and sales. The selection of the brand ambassador is a strategic decision with direct implication on the brand equity. A strong celebrity–brand congruence is ideal to establish credibility, but it can backfire if anything negative occurs on either side. This case evaluates the crisis faced by Fortune oil which has been positioned as “the heart healthy oil” when its celebrity ambassador suffers heart attack. In the backdrop of the case, the students can analyse brand strategies with respect to ambassador marketing, TEARS model with No TEARS approach for endorser selection and endorser-related credibility risk management.

MBA BBA PG/Graduation in Marketing/Advertising.

Teaching Notes are available for educators only.

CSS 8: Marketing.

The estimation of market value of intangible benefits of afforestation has always been a challenging task, and the contingent valuation method is a popular method used in environmental assessment. The NTPC set up a coal-based power plant in Korba, India and planted 1.6 million trees on 19% of the project area.

The individual's mean and median willingness to pay (WTP) for four intangible benefits, namely, pollution control (PC), improvement in underground water level (IUGWL), soil conservation and remediation (SCR) in addition to total WTP from the afforestation program of NTPC were estimated using a customized procedure for logit model based upon respondent's age, education, occupation, income and bid amount asked to pay. Stratified multistage random sampling has been used to select the respondents.

The procedure increases the number of respondents who are willing to pay as compared to conventional CVM. The finding of the study shows that the highest WTP was observed for PC (Rs. 462.84 per month per household) followed by SCR and IUGWL, whereas for total WTP it was Rs. 972.60.

The proposed customized procedure and the results thereof would be useful in improving the WTP estimates for other similar studies in order to conserve the environment.

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.

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.

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.

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.

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.

The increase in automobile usage across the world has fortified the opportunities of maintenance service garages. However, there are significant numbers of challenges in front of maintenance service providers at all stages of the business. This paper identifies, analyzes and prioritizes various challenges associated with the establishment and survival of garages specific to Indian context.

In this paper, challenges for automotive service garage are identified through expert opinion, garage survey and literature. A structural hierarchical framework of the identified challenges is established through structural models, including interpretive structural modeling and analytic hierarchy process.

This paper has identified nine challenges, namely proliferation of new models and variants; technological advancements in automobile systems; demand of better service quality; space and ambience requirements; labor requirements; requirement of modern support equipments, tools and spares; safety requirements and prevention of occupational hazards; environmental norms and concerns; proper documentation requirements. The drivers and dependent variables have been identified. A hierarchical framework of challenges has been established.

This paper provides a comprehensive list of challenges and their priority in establishing an automobile maintenance garage business in Indian context. This will help the budding entrepreneurs and existing maintenance organizations to focus on the challenges that necessitate immediate attention and corrective actions.

This paper provides a significant contribution in the literature of garage maintenance services, which is established on the viewpoint of different collaborators associated with this business. This study will be a foundation to investigate further in this domain.

The study aims to evaluate and compare the mergers and acquisitions (M&As) performance utilising a sample of deals originating from Brazil, Russia, India, China and South Africa (BRICS). In addition to nation-wise performance analysis, a further sub-sample analysis is conducted based on the target location (domestic and cross-border), development status (developed and emerging) and the acquired ownership stakes (majority and minority).

The final sample of the study includes 7,105 deals announced between 2000 and 2019. M&A performance is proxied by the abnormal returns earned over the select event windows. Multiple parametric and non-parametric tests are employed for testing the robustness.

The results indicate significant performance differences across BRICS markets, with the highest and lowest abnormal returns reported for Chinese and Russian acquirers, respectively. The disaggregated analysis also affirms the performance differences for the select sub-samples.

The study highlights the need for acknowledging and expounding the differences in M&As across emerging markets. Further, the results of the study provide a possible explanation of the disagreement over the M&A performance results reported in the previous literature.

Acknowledging and understanding the potential performance differences based on location, ownership strategies and development status can aid executives in sharpening decision-making and also help general investors.

The study contributes by examining a comprehensive sample of deals across five major emerging economies, as against the majority of previous studies which have their results based on either single nation samples or have utilised only a sub-sample of domestic or foreign acquisitions.

The helical spring lock washer (HSLW) is a part of nut bolt joint assembly used in different industries like automobile, aerospace, mechanical, chemical, electrical, electronics, etc. It works as a part of temporary joint and plays important role in loosening behavior of assembly under dynamic (vibrations) conditions. Thus, the purpose of this paper is to investigate the performance of HSLW under different controlled operating conditions in order to satisfy its functional requirement.

In the present investigation, a novel test rig is designed and developed to determine the load-deflection characteristics of HSLWs. The test rig facilitates the controlled linear displacement of the HSLW with predetermined angular rotation of the handle gives the corresponding reaction load on the display. Additionally, the repeatability and reproducibility of the test rig was carried out.

The newly designed and developed test rig is capable enough to differentiate the load-deflection characteristics during compressive loading and unloading of HSLWs. Additionally, the loss of strain energy can be determined from the load-deflection characteristics of HSLW.

The present test rig is designed and developed to investigate the load-deflection characteristics under compressive loading and unloading of HSLW. The test rig has least count of 0.4905 N for load measurement and 0.01389 mm for linear displacement.

This paper aims to understand how organizations can apply the Blue Ocean Shift process to achieve profitable growth and make competition irrelevant.

This paper uses a case study approach. Based on interaction with the senior management of an organization and secondary sources, this paper presents an application of the Blue Ocean Shift process on a strategic move by an organization to achieve value innovation.

This paper presents a case of how Tata Motors Ltd. applied Blue Ocean Shift process to come up with the product Tata Ace, which achieved value innovation while making competition irrelevant. From assessing the current state of play to forming a motivated team, working with suppliers and fulfilling the needs of the non-customers and unhappy existing users, they were able to create a strong position for themselves.

Blue Ocean Strategy, through a process defined as Blue Ocean Shift, can be applied by organizations to achieve value innovation, change market boundaries and achieve profitable growth through their strategic offerings. It can help them get out of “red oceans” which may be a way to view the existing hypercompetitive world.

This paper contributes to the application of the Blue Ocean Shift process in the Indian context while studying a strategic move of an Indian firm. It showcases an example of how large Indian organizations can successfully apply the process to achieve value innovation.

This study aims to examine the impact of home–host country distance on the cross-border mergers and acquisitions performance.

The results of this study are based on a final sample of 483 completed cross-border deals involving BRICS nation acquirers and targets spread across a set of 27 nations. While controlling for prior experience, among other factors, the impact of nine institutional distance dimensions on deal performance is examined. Cumulative abnormal returns calculated over the select event windows are used as a measure of deal performance.

The results of this study validate the explanatory power of cross-country distance and exhibit that financial and cultural distance exert a negative influence on deal performance, whereas political and global connectedness distance positively impacts performance. Interestingly, geographic distance is not found to be related to performance outcomes.

The results of this study caution against possible aggregation of the cross-country distance measure and point towards the need to acknowledge and analyse the multi-dimensional nature of distance.

The results of this study are expected to aid managers in devising internationalisation strategies and target selection, maximising their performance and shareholder wealth.

This study contributes to the knowledge of internationalisation and cross-country distance. It presents as one of the first to investigate the impact of institutional distance on deal performance using a substantially large multi-country emerging market data set.

The purpose of this study is to select the appropriate forecasting model at the retail stage for selected vegetables on the basis of performance analysis.

Various forecasting models such as the Box–Jenkins-based auto-regressive integrated moving average model and machine learning-based algorithms such as long short-term memory (LSTM) networks, support vector regression (SVR), random forest regression, gradient boosting regression (GBR) and extreme GBR (XGBoost/XGBR) were proposed and applied (i.e. modeling, training, testing and predicting) at the retail stage for selected vegetables to forecast demand. The performance analysis (i.e. forecasting error analysis) was carried out to select the appropriate forecasting model at the retail stage for selected vegetables.

From the obtained results for a case environment, it was observed that the machine learning algorithms, namely LSTM and SVR, produced the better results in comparison with other different demand forecasting models.

The results obtained from the case environment cannot be generalized. However, it may be used for forecasting of different agriculture produces at the retail stage, capturing their demand environment.

The implementation of LSTM and SVR for the case situation at the retail stage will reduce the forecast error, daily retail inventory and fresh produce wastage and will increase the daily revenue.

The demand forecasting model selection for agriculture produce at the retail stage on the basis of performance analysis is a unique study where both traditional and non-traditional models were analyzed and compared.

Regardless of the diverse research on big data analytics (BDA) across different supply chains, little attention has been paid to exploit this information across service supply chains. The healthcare supply chains, where supply chain operations consume the second highest expenditures, have not completely attained the potential gains from data analytics. So, this paper explores the challenges of BDA at various levels of healthcare supply chains.

Drawing on the resource-based view (RBV), this research explores the various challenges of big data at organizational and operational level of different nodes in healthcare supply chains. To demonstrate the links among supply chain nodes, the authors have used a supplier-input-process-output-customer (SIPOC) chart to list healthcare suppliers, inputs (such as employees) supplied and used by the main healthcare processes, outputs (products and services) of these processes, and customers (patients and community).

Using thematic analysis, the authors were able to identify numerous challenges and commonalities among these challenges for the case of healthcare supply chains across United Arab Emirates (UAE). An applicable exploration on organizational (Socio-technical) and operational challenges to BDA can enable healthcare managers to acclimate efficient and effective strategies.

The identified common socio-technical and operational challenges could be verified, and their impacts on the sustainable performance of various supply chains should be explored using formal research methods.

This research advances the body of literature on BDA in healthcare supply chains in that (1) it presents a structured approach for exploring the challenges from various stakeholders of healthcare chain; (2) it presents the most common challenges of big data across the chain and finally (3) it uses the context of UAE where government is focusing on medical tourism in the coming years.

Originality of this work stems from the fact that most of the previous academic research in this area has focused on technology perspectives, a clear understanding of the managerial and strategic implications and challenges of big data is still missing in the literature.

Individuals generate plenty of waste that is affecting the life while consumption of air and water at the base. The increasing industrialization, population and waste generation without proper measures of waste management are leading to major challenges to environmental sustainability. Considering these challenges, the present study focuses on the types and sources of waste generation and waste reduction by encouraging the reduction, recycling and reuse of waste products. The study aims to provide a well-functioning sustainable waste management system, that incorporates feedback loops, focuses on processes, embodies adaptability and diverts waste from disposal.

The university under study is situated at the central location of Pune City in India. The university has diverse units like academic and admin buildings, canteens and mess, hostels, a clinic, workshops and gardens. To fulfil the objective of this study a qualitative case study approach of research was adopted. A total of thirty-three representatives and waste management personnel from various units of the university were interviewed. The interviews were semi-structured and the duration of it was around 25–55 min. The interview transcripts were coded, and qualitative analysis was conducted.

This study proposes a strategic sustainable waste management model for environmental sustainability that brings circularity by closing the loops and focusing on sustainable development goals.

The findings of this research can guide universities to manage the waste generated through various sources and attain sustainable development goals and environmental sustainability at large by closing the loops. The study provides insights into waste management and environmental sustainability. The universities can make their resources more circular by following the strategies of reducing, reusing and recycling (3R). This study recommends customization according to the needs of specific universities and institutions. Researchers can take this study further by testing and customizing it as per requirement. Also, an effort can be extended to implement the model in other related areas.

This research is a unique attempt to advance knowledge of waste management practices for sustainable development by exploring different techniques opted by for individual entities from the university campus to understand the environmental impact.

The purpose of the present study was to investigate the interrelationships among the dimensions of sport event experience, event satisfaction and event behavioral intentions.

The sample was comprised of 186 individuals who actively participated in a mass participation sport event. Partial least squares-structural equation modeling (PLS-SEM) was employed to test the relationships among the latent constructs.

The results indicated that the dimensions of sport event experience predicted 55% of the variance of event satisfaction and 63% of the variance of event behavioral intentions was predicted by sport event experience dimensions and event satisfaction. Specifically, the sensory, affective and relational dimensions of experience sought to have a statistically significant and positive association with event satisfaction, while event satisfaction and the relational dimension of experience were found to have a statistically significant and positive correlation with event behavioral intentions. In addition, event satisfaction was found to mediate the relationships between sensory, affective and relational experiences and event behavioral intentions.

The present study is one of the first that explores the relationships among sport event experience’s dimensions, event satisfaction and positive behavioral intentions in the context of sport event participation.

The aim of this paper is to assess the service quality of a small airline, Air Mauritius, using the SERVQUAL model and to determine the relative importance attributed to service quality dimensions by international tourists.

A sample of 140 international airline passengers travelling essentially for a leisure trip was administered the SERVQUAL instrument to determine their expectations and perceptions of service. A combination of in‐flight and mail surveys was used for data collection leading to an overall response rate of 20.2 per cent.

The paper finds that service quality structural dimensions are context‐ and culture‐specific. Four factors are perceived as influencing perceptions of service, service efficiency and affect being the most important, service personalisation, reliability and tangibles the least important. Empathy as a service dimension is valued more than assurance. Customer satisfaction and willingness to recommend the airline is primarily dependent on service efficiency and affect.

The sample size is relatively small and biased towards South African passengers, but the study is exploratory in nature. The starting‐point for service improvements at Air Mauritius is better management of service reliability. The company is able to create high perceptions of service using tangible cues.

The generation of a vision of excellence supported by contact employees' empowerment should improve perceptions of service. There is potentially a link between expectations of service levels at destination and tourists' expectations from the flag carrier.

Often smaller airline companies have to resort to strategic alliances and service differentiation to survive in this globally integrated industry. The paper fulfils the gap in the existing literature on service quality management in small airlines.

The purpose of this paper is to identify the dimensions of customer expectations and study the moderating role of demographics in the context of fresh food retail.

A structured questionnaire was designed using extant literature review followed by expert opinions. The survey was conducted among the customers in the twin cities of Maharashtra in India. The factors of customer expectations were identified using exploratory factor analysis (EFA) and further confirmed using confirmatory factor analysis in SPSS and AMOS, respectively. The significance of the customer expectations on customer satisfaction was studied using structural equation modeling. Subsequently, the role of demographics was studied using two-step cluster analysis and multigroup moderation.

During EFA three factors emerged, namely, product-related features, in-store quality and store support services. Structural model evaluation found product-related features and in-store quality significantly influencing the customer satisfaction, while store support services were found as a non-significant factor in the region studied. Further, using cluster analysis customers were segregated into three groups, namely, traditional, autonomous and premium customers, where the premium customers were found to prefer the store support services on a higher scale, and similar results were obtained using multigroup moderation. Demographics, namely, gender, age, respondents’ income and marital status moderated for product-related features and in-store quality. Interestingly, respondents’ income also moderated for the store support services.

The findings provide directions for store managers of the fresh food category to align supply chain decisions with the unique requirements of customers considering their socio-economic characteristics.

On the basis of social exchange theory, the authors found that in a mutually beneficial relationship, concerning the value proposition, retailers need to address the requirement of the different income group customers for store support services.

The purpose of this paper is to give a brief introduction of helical spring locked washer along with extensive literatures survey on role of helical spring locked washer in bolted joint analysis. It is very small component of bolted joint assembly, but it play vital role in holding the assembly components together. Helical shape of it produces spring effect in the assembly which is used for keeping the assembly in tension and that is lock the assembly under dynamic loading due to vibrations to avoid the accident.

The critical literatures survey identifies role of helical spring locked washer in different areas such as design optimization, mechanism of loosening-resistant components, bolted joint analysis, finite element-based modeling, analysis and simulation. The related literatures show contribution of helical spring washers in evaluation of anti-loosening performance of assemblies as compare to other types of washers.

It proposed that design optimization of helical spring locked washer is needed as it improves the performance in the form of load-deflection characteristics, load bearing capacity and provides the best locking force for optimize functionality.

The originality or value of this paper is to finding research gaps in literatures by dividing literatures into seven different research areas and concentrating the only on role of helical spring locked washer in bolted joint analysis.