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The purpose of this paper is to investigate the optimized setting of wire-cut electrical discharge machining (WEDM) parameters at which material removal rate (MRR) and mean roughness depth (Rz) set a compromise. The problem in the processing of Ti-6Al-4V by conventional processes is a high strength, high hardness, high tool wear. Due to which WEDM is adopted to machine Ti-6Al-4V biomedical alloy. Ti-6Al-4V alloy has a number of applications in the engineering and medical industries due to its high strength biocompatibility.

The effect of control factors (i.e. pulse on-time: Pon; pulse off-time: Poff; servo voltage: SV) on the MRR and Rz is investigated in the present research. The planning of experiments is done using a Taguchi-based L9 orthogonal array. The percentage influence of each factor on responses is also evaluated. The multi-objective optimization is done using the grey approach initially. After that, the results were also calculated using harmony search (HS). Therefore, a hybrid approach of grey and HS is used to find the optimized values of MRR and Rz.

The maximum value of grade calculated by grey-HS is 0.7879, while in the case of the experimental run the maximum value of grey grade is 0.7239. The optimized setting after improvisation at this grade value is Pon: 130 µs; Poff: 45 µs and SV: 70 V for MRR and Rz collectively. The validation of the suggested setting is completed by experimentation. The values of MRR and Rz are coming out to be 6.4 mm³/min and 13.84 µm, which represents improvised results after the implementation of the HS algorithm.

The integration of the grey approach with the HS principle in the manufacturing domain is yet to be explored. Therefore, in the present research hybrid approach of grey-HS is implemented in the manufacturing domain having applications in medical industries.

The purpose of this study is to investigate the role of blockchain technology in reducing online fraud among Gen Y and Gen Z.

This study uses a two-phase approach. Firstly, a systematic literature review is conducted to examine various aspects of blockchain technology and cyber security. Secondly, the Technology Adoption Model is used to study the adoption dynamics of blockchain-based platforms for online data exchange among 415 Gen Y and Z users.

The results indicate that efficiency and security, perceived ease of use, perceived usefulness, and trust have a positive effect on behavioral intention and attitude towards use. This is the first study to examine the role of blockchain technology to reduce fraud among Gen Y and Gen Z.

This study provides new insights into the adoption of blockchain-based platforms for online data exchange among Gen Y and Gen Z. The study highlights the critical areas of concern for the adoption of blockchain technology and provides managerial implications for fintech firms, banks, and e-commerce platforms. It is unique in its focus on the potential for blockchain technology to reduce fraud among Gen Y and Gen Z, which has not been previously explored in the literature.

The purpose of this study is to examine the trends and developments of subscription business models (SBMs) over the past two decades.

The study extracted 469 documents (articles and reviews) from the Scopus database during 2000–2022 and analysed 132 documents (articles and reviews). A bibliometric methodology of scientific mapping was employed, including a cluster analysis based on the bibliographic coupling of documents. Content analysis was also conducted to reveal emerging trends in SBMs.

The study revealed six emerging themes in SBMs related to consumer behaviour, digital advertising, online news media, journal publications, circular economy and sustainability strategies.

The results of this study provide new and unique insights into the development and trends of SBMs over the past two decades and offer guidance for future researchers to investigate further the phenomenon of SBMs in emerging areas.

The food organisations are pushing to adopt circular economy initiatives to enhance economic–ecological–social sustainability of supply chains. The adoption of circular economy and sustainability aspects is complex from the point of view of developing nations compared to the developed nations. In this sense, the purpose of this paper is to develop a model of the challenges for implementing the successful circular economy-led sustainability concepts in food supply chains in emerging economies, especially in the Indian context.

The authors recognised 11 circular economy-led sustainability-related challenges and analysed appropriate interactions among the identified challenges. The Delphi method was used for the confirmation of identified challenges. The challenges were identified initially with the help of literature. Interpretive structural modelling method was used for modelling the challenges. In addition, MICMAC analysis was used for classifying the challenges based on their dependence and driving power. A case study of diary food processing company in India was conducted.

According to the findings, poor government policies, lack of technology and techniques and lack of farmers’ knowledge and awareness come under the driving challenges.

Understanding of circular economy-led sustainability-related challenges would help managers and policy makers in the sustainable management of natural resources in food value chains.

This is one of the initial works conducted on identifying and evaluating the challenges to circular economy-based sustainability aspects in food value chains.

The purpose of this study is to identify the accelerators of sharing economy that lead to sustainability by adopting green consumption. Nostalgia is studied as a mediator along with social connectedness and past orientation. Specifically, the study is based upon a framework to explore the outcomes of sharing economy through an individual's green consumption behavior from the perspective of mortality anxiety.

Quantitative research technique was employed by collecting data from 537 households through snowball sampling. The model was tested using partial least squares (SEM-VB). The validity of the theoretical and measurement model was assessed.

The results revealed that nostalgia positively influences social connectedness and past orientation, whereas social connectedness and past orientation accelerate green consumption. However, it was confirmed that nostalgia decreases green consumption.

The drivers of sharing economy lead toward environmentally friendly consumer behavior by providing opportunities for different agents to increase the usage of shared consumption. The model can be improved by introducing other mediating variables to enrich understanding.

The study may provide opportunities for practitioners and the government to identify the key factors in a sharing economy, specifically with reference to green consumption and social connectedness. It is predicted that it will help reduce environmental deterioration.

This study identifies the role of mortality anxiety and nostalgia toward green consumption, predominantly in the context of a sharing economy. It is a forward to collaborative consumption.

This research focuses on suggesting an optimized model for selecting best employees using advanced multi-criteria decision making method to a supply chain firm, who is planning to start a new cold chain business vertical.

Study has been conducted in a supply chain firm in North India, who wants to expand its business with the help of efficient team members. In total 38 applicants were considered for the study, as selected by the firm after initial screening from pool of talent. AHP-LP and TOPSIS-LP integrated approach were applied separately for evaluation and implementation of personnel selection model. Further, both the approaches were compared to find the best fit and optimized model.

As per the findings, both AHP and TOPSIS can be used to select the best candidate among the alternatives available. TOPSIS was found easier to implement as it involves ranking of applicants with respect to each skills required for respective job profile only once, whereas AHP involves pair-wise comparison among candidates with respect to each skills required for respective job profile and normalization of each comparison, resulting in the formation of number of comparison matrices. However, AHP is more reliable as it considers consistency check for each level of pair-wise comparison. Hence, there is a chance to avoid or revise the human judgment error. Integrated ranking and optimization approach minimizes the cost by suggesting the relevant positions to be filed to make an efficient team.

Group of interviewers are involved in the decision-making process, hence there are chances of biasness in ranking method which can influence the group decision. Research is limited to a particular geography of North India therefore needs to be tested for other regions also in order to generalize. The research will help the third party logistics (3PL) and other related firms in efficient team selection.

The researcher focuses on formalizing a method for potential candidate selection by considering the constraints of the organization. It has been observed that limited researches have been done on the application of AHP-LP or TOPSIS-LP integrated approach for selection process. Hence, this research proposes two integrated ranking-optimization method and suggests the best fit by comparing both the approaches.

This paper aims to take stock of research done in the domain of relationship marketing (RM). Additionally, this article aims to identify the potential areas of future research.

The authors have used machine learning-based structural topic modelling using R-software to analyse the dataset of 1,905 RM articles published between 1978 and 2020.

Structural topic modeling (STM) analysis led to identifying 14 topics, out of which 7 (viz. customer loyalty, customer relationship management systems, interfirm and network relationships, relationship selling, services and relationship management, consumer brand relationships and relationship marketing research) have shown a rising trend. The study also proposes a taxonomical framework to summarize RM research.

This is the first comprehensive review of RM research spanning over more than four decades. The study’s insights would benefit future scholars of this field to plan/execute their research for greater publication success. Additionally, managers could use the practical implications for achieving better RM outcomes.

This paper aims to evaluate the effects of inulin (3 per cent), chitosan (1 per cent) and carrageenan (0.5 per cent) addition on the physico-chemical, sensory and textural attributes of restructured goat meat products. Health conscious consumers are much more interested in product with added health benefit. Keeping this in mind, this study was undertaken to find out effective ingredient for low fat restructured goat meat product.

Formulation for restructured goat meat blocks was optimized and four different formulation containing different ingredients, namely, control, inulin (3 per cent), chitosan (1 per cent) and carrageenan (0.5 per cent), were used to find out best ingredient for healthier goat meat product and various physicochemical and sensory properties of the product were evaluated.

Results showed that addition of carrageenan improved (p < 0.01) the product yield (86.0 per cent) significantly. The proximate composition, expressible water and water activity were similar. The moisture retention percentage was significantly (p < 0.01) reduced (86.0 per cent) due to addition of inulin. Carrageenan significantly (p < 0.05) increased the lightness (42.4) and yellowness (10) values. Significantly (p < 0.05) lower shear force values were observed in inulin (0.5) and chitosan (0.4) containing samples than control (0.7 kg/1.5 cm²). Hardness values were significantly (p < 0.05) lower in restructured product containing chitosan (56.1 N/cm²) and carrageenan (59.4 N/cm²). Similarly, springiness values were significantly (p < 0.05) lower (0.7 vs 0.8 cm) in carrageenan containing product. Inulin, chitosan and carrageenan did not significantly influence the sensory attributes of restructured goat meat product. It is concluded that inulin, chitosan and carrageenan could be used to improve technological and functional attributes of the healthier restructured goat meat product.

Future research may benefit from efforts to modify shelf life of the product by modifying packaging condition.

The healthier meat-based restructured goat meat product has been developed, and the effect on its quality characteristics have been extensively examined, limited research has focused on this aspect.

The crowdfunding concept and activities have recently been the focus of attention of many researchers and practitioners over different business contexts. However, there is a dearth of literature considering the main aspects of e-equity crowdfunding activities and their impact on the innovation performance for entrepreneurial business. Therefore, this study aims to explore how entrepreneurs' engagement in e-crowdfunding activities could enhance both knowledge acquisition and innovation performance.

The conceptual model will be proposed based on three main theoretical perspectives: relationship marketing orientation (RMO); Kirzner's alertness theory; and the DeLone and McLean model of information systems. The data of the current study were collected using an online questionnaire from a sample of 500 entrepreneurs who have actively engaged in e-crowdfunding in Saudi Arabia.

The statistical results of structural equation modelling (SEM) approved the impacting role of RMO, entrepreneurial alertness, system quality and service quality on the entrepreneurs' engagement in e-equity crowdfunding, which in turn, predicts both knowledge acquisition and innovation performance.

There are several limitations which could be addressed in future studies, for example, this study has only considered one form of crowdfunding (equity based crowdfunding) and due to its nature these findings would not be easily generalized to other kinds of crowdfunding (i.e. donation-based crowdfunding; rewards-based crowdfunding; and debt-based crowdfunding). Future studies could consider these kinds of crowdfunding activities.

This study has contributed to the understanding of e-equity crowdfunding in several aspects. For example, this study presents results that assist both researchers and practitioners in the Middle East and Saudi Arabia to develop an in-depth knowledge of e-equity crowdfunding by considering new dimensions such as RMO and information system success factors.

The increasing popularity of live-streaming commerce has provided a new opportunity for e-retailers to boost sales. This study integrated signaling theory and social exchange theory to investigate how streamer- and product-centered signals influence customers’ likelihood of making an impulsive purchase in the live-streaming commerce context.

An online survey was designed and distributed to the target respondents in China using purposive sampling. A total of 735 valid responses were analyzed with partial least square structural equation modeling (PLS-SEM).

Both streamer-centered signals, i.e. streamer credibility and streamer interaction quality, were discovered to significantly influence product-centered signal, i.e. product information quality. Additionally, streamer interaction quality was found to have a significant impact on streamer credibility. Furthermore, it was observed that customer engagement played a significant mediating role in the relationship between product information quality and impulsive buying tendency. Moreover, the paths between product information quality and customer engagement, as well as the connection between engagement and impulsive buying tendency, were found to be moderated by guanxi orientation.

Despite the prevalence of impulsive purchases in live-streaming commerce, few studies have empirically investigated the impact of streamer and product signals on influencing customers’ impulsive purchase decisions. Consequently, to the best of our knowledge, this study distinguishes itself by offering empirical insights into how streamers use reciprocating relationship mechanisms to communicate signals that facilitate impulsive purchase decisions.