Search results

The purpose of this paper is to design a modified version of the double sampling plan to handle the inspection processes requiring a minimum sample size to assure the median life for the products under the new Weibull–Pareto distribution. The economic design of the proposed plan is also considered to assure the product's lifetime with minimum cost.

The authors have developed an optimization model for obtaining the required plan parameters by solving simultaneously two non-linear inequalities and such inequalities have been formed based on the two points on the operating characteristic curve approach.

The results show that the average sample number, average total inspection and total inspection cost under the proposed plan are smaller than the same of a single sampling plan. This means that the proposed plan will be more efficient than a single sampling plan in reducing inspection effort and cost while providing the desired protection.

The proposed modified double sampling plan designed to assure the median life of the products under the new Weibull–Pareto distribution is not available in the literature. The proposed plan will be very useful in assuring the product median lifetime with minimum sample size as well as minimum cost in all the manufacturing industries.

This study aims to explore the adoption behaviour of consumers towards innovative technology products and services (ITPS).

A qualitative study using semi-structured in-depth interviews was conducted with 47 respondents. Their lived experiences across 50+ ITPS were studied. A grounded theory approach was used to develop a theory with reference to consumer adoption of ITPS.

Themes emerged across the adoption process, such as triggers for adoption (pressing need, making life more pleasurable, urge to acquire and forced initiation); hesitancies faced by consumers during evaluation (value alignment, utilization, ecosystem, risks with new technology and price); and factors that help in overcoming the hesitancies (word of mouth, de-risking schemes and self-devised strategies).

Innovators must understand customer triggers and design offerings that activate the same – addressing a pressing need or making lives more pleasurable. Users driven purely by an urge to acquire can be a source of early word of mouth for radical innovations. Innovations must be designed and communicated to minimize hesitancies. Mitigating schemes such as equated monthly installment and return policy can be offered to empower customers to overcome hesitancies. Factors such as price, risk, beliefs, traditions and nationalistic values assume importance, specifically in an emerging economy.

This study based on grounded theory keeps the user at the centre and explains the innovation adoption phenomenon for a wide variety of 50+ ITPS in the context of an emerging economy.

This study aims to explore the factors influencing the bottom of the pyramid (BOP) consumers’ adoption and usage intention towards mobile payment (m-payment) to achieve financial inclusion and sustainable development goals.

A qualitative research design is used to explore the enablers and inhibitors that influence BOP consumers’ m-payment adoption and usage intention. To collect the qualitative responses, semi-structured in-depth interviews with BOP respondents were conducted. The thematic analysis using the text mining technique will be used to analyse qualitative data for exploring the predominant factors affecting m-payment adoption intention and usage.

The results suggested awareness, social influences and self-efficacy as crucial enablers and privacy and security risks and vulnerability concerns as crucial inhibitors towards m-payment adoption and usage.

As a novel contribution to the BOP, financial inclusion, sustainable development goals and m-payment literature, this study unfolds several unknown perceived benefits and perceived sacrifices that influence the BOP consumers’ m-payment adoption intention and usage. The study’s findings help the government and banks formulate and implement strategies to achieve financial inclusion among BOP consumers.

The aim of this research was to investigate fans’ responses toward a sponsor that has had a long-standing sponsorship deal with a club and decided also to sponsor the club’s rival.

A long-term sponsorship deal between a retsina wine company and a popular football club and a newly established deal between the company and the main rival club were selected as the research setting. Data were collected from a total sample of 302 participants, fans of the two teams, using an online survey and PLS-SEM was employed to test the relationships of the proposed structural model.

The results provided evidence for the importance of the inclusion of perceptions of fit for both teams to the model as it impacted the responses in the joint sponsorship. Team identification emerged significant for improving fans perceptions of fit between the sponsor and their favorite club but also led fans of the long-term sponsored club to feel betrayed from the sponsor. The sense of betrayal impacted the level of fit, the rejection of sponsorship but did not emerge significant for driving negative responses toward the sponsor’s brand. The same held for the rejection of the joint sponsorship.

This is the very first study that incorporated the effects of the perceptions of fit of two rival clubs to test the effect of sponsorship for a sponsor brand of a deal that includes a longtime sponsored football club and its rival as a newly sponsored one. It is also one of the first attempts that explores relationships between perceptions of fit, sense of betrayal and rejection of a joint sport sponsorship in a rivalry context, highlighting the importance of preventing fans' betrayal.

This study aims to address the inherent uncertainties within closed-loop supply chain (CLSC) networks through the application of a multi-objective approach, specifically focusing on the optimization of integrated production and transportation processes. The primary purpose is to enhance decision-making in supply chain management by formulating a robust multi-objective model.

In dealing with uncertainty, this study uses Pythagorean fuzzy numbers (PFNs) to effectively represent and quantify uncertainties associated with various parameters within the CLSC network. The proposed model is solved using Pythagorean hesitant fuzzy programming, presenting a comprehensive and innovative methodology designed explicitly for handling uncertainties inherent in CLSC contexts.

The research findings highlight the effectiveness and reliability of the proposed framework for addressing uncertainties within CLSC networks. Through a comparative analysis with other established approaches, the model demonstrates its robustness, showcasing its potential to make informed and resilient decisions in supply chain management.

This study successfully addressed uncertainty in CLSC networks, providing logistics managers with a robust decision-making framework. Emphasizing the importance of PFNs and Pythagorean hesitant fuzzy programming, the research offered practical insights for optimizing transportation routes and resource allocation. Future research could explore dynamic factors in CLSCs, integrate real-time data and leverage emerging technologies for more agile and sustainable supply chain management.

This research contributes significantly to the field by introducing a novel and comprehensive methodology for managing uncertainty in CLSC networks. The adoption of PFNs and Pythagorean hesitant fuzzy programming offers an original and valuable approach to addressing uncertainties, providing practitioners and decision-makers with insights to make informed and resilient decisions in supply chain management.

Vehicle allocation problems (VAPs), which are frequently confronted in many transportation activities, primarily including but not limited to full truckload freight transportation operations, induce a significant economic impact. Despite the increasing academic attention to the field, literature still fails to match the needs of and opportunities in the growing industrial practices. In particular, the literature can grow upon the ideas on sustainability, Industry 4.0 and collaboration, which shape future practices not only in logistics but also in many other industries. This review has the potential to enhance and accelerate the development of relevant literature that matches the challenges confronted in industrial problems. Furthermore, this review can help to explore the existing methods, algorithms and techniques employed to address this problem, reveal directions and generate inspiration for potential improvements.

This study provides a literature review on VAPs, focusing on quantitative models that incorporate any of the following emerging logistics trends: sustainability, Industry 4.0 and logistics collaboration.

In the literature, sustainability interactions have been limited to environmental externalities (mostly reducing operational-level emissions) and economic considerations; however, emissions generated throughout the supply chain, other environmental externalities such as waste and product deterioration, or the level of stakeholder engagement, etc., are to be monitored in order to achieve overall climate-neutral services to the society. Moreover, even though there are many types of collaboration (such as co-opetition and vertical collaboration) and Industry 4.0 opportunities (such as sharing information and comanaging distribution operations) that could improve vehicle allocation operations, these topics have not yet received sufficient attention from researchers.

The scientific contribution of this study is twofold: (1) This study analyses decision models of each reviewed article in terms of decision variable, constraint and assumption sets, objectives, modeling and solving approaches, the contribution of the article and the way that any of sustainability, Industry 4.0 and collaboration aspects are incorporated into the model. (2) The authors provide a discussion on the gaps in the related literature, particularly focusing on practical opportunities and serving climate-neutrality targets, carried out under four main streams: logistics collaboration possibilities, supply chain risks, smart solutions and various other potential practices. As a result, the review provides several gaps in the literature and/or potential research ideas that can improve the literature and may provide positive industrial impacts, particularly on how logistics collaboration may be further engaged, which supply chain risks are to be incorporated into decision models, and how smart solutions can be employed to cope with uncertainty and improve the effectiveness and efficiency of operations.

This paper aims to examine the options available to arbitrators when they suspect money laundering during arbitration proceedings, considering their compatibility with fundamental principles and concepts of arbitration.

Using a doctrinal analysis approach, the paper draws on legal principles, antimoney laundering regulations and relevant literature to explore the topic. It considers relevant international treaties, standards set by the financial action task force on money laundering, cases and arguments from legal analysts and experts.

The paper identifies three options for arbitrators: disregarding suspicions, initiating an investigation or terminating the proceedings. Disregarding suspicions is deemed inappropriate, as it may facilitate the concealment of financial crimes. Initiating an investigation is seen as a preferable option, aligning with the arbitrator’s role and the public interest in nullifying contracts linked to criminal conduct. Terminating the proceedings is not recommended, as it contradicts the principle of natural justice. The paper emphasizes the importance of reasonable grounds for suspicions, notifying the parties, and allowing them to address the concerns.

This paper contributes to the existing literature by comprehensively analyzing the compatibility of these options with arbitration principles and concepts. It underscores the need for clear laws and directives to guide arbitrators in addressing financial crimes within the arbitration process, maintaining a balance between party autonomy and preventing the misuse of arbitration for illicit activities.

This paper aims to examine the antecedents of adoption intention of profit-sharing investment deposits (PSID) among Moroccan customers.

Applying an extended version of diffusion of innovation (DOI) theory and using a non-probability sampling technique with convenience approach, a quantitative survey was developed and administered to 171 Islamic banking users. Structural equation modeling was then used to evaluate the significance of relationships between the various variables under study using SPSS 21.0 and AMOS 26.0 statistical packages.

Empirical findings of the structural analysis indicated a significant direct relationship between adoption intention and six out of seven variables: perceived relative advantage, perceived compatibility, perceived complexity, perceived risk, religiosity and social influence, all of which had a significant effect on Moroccan customers’ intention to invest their funds in profit-sharing based deposit instruments, whereas customer awareness exerted an insignificant positive effect.

The absence of a longitudinal study tracking the actual adoption behavior is the main limitation of this study. Furthermore, data were collected solely from Islamic banking users. Finally, despite being insightful, the empirical findings should be generalized with caution since the sample was purposely selected by the banks’ management.

This study implied that participatory banks should pay substantial attention to risk perceptions, as PSID adoption intention is typically inhibited by high perceived risks associated with these products. Moreover, this study provides great indications to Moroccan regulators and policymakers on a number of issues related to this emerging business.

To the best of the authors’ knowledge, this paper represents the first attempt to confirm the effectiveness of the Rogers’ DOI in examining the intention to adopt a financial innovation in the Moroccan context. It is also the first of its kind to address customers’ apprehensions regarding profit-sharing investment products.

This paper presents a comprehensive decision-making framework designed for family-owned hotels, specifically focusing on evaluating and selecting suppliers and strategic partners, with a particular emphasis on Iranian holding companies and five-star hotels.

The research emphasizes the unique position of family-owned hotels as not only commercial enterprises but also embodiments of tradition, personal touch and community engagement, which sets them apart in a competitive market. Through a detailed literature review, methodology and analysis, including fuzzy analysis and the TOPSIS method, the study systematically evaluates various criteria crucial for selecting suppliers and strategic partners.

The framework evaluates criteria such as price competitiveness, quality of products/services, reliability and timeliness, flexibility and scalability, communication and responsiveness, after-sales service and support, ethical and sustainable practices, technology and innovation, and compatibility with business culture. By integrating these parameters, the framework addresses both operational needs and strategic objectives, ensuring chosen suppliers and partners align with the hotels' core values and operational requirements.

The study offers valuable insights for family-owned hospitality businesses to navigate supplier and strategic partner selection, and opens avenues for future research, particularly in adapting to technological advancements, sustainability practices and the evolving dynamics of the hospitality industry.

The research underscores the significance of family-owned hotels in fostering tradition, personal connection and community engagement, contributing to the social fabric of the hospitality industry.

This paper provides a unique perspective on supplier and strategic partner selection, tailored for family-owned hotels and offers a comprehensive framework that integrates both operational needs and strategic objectives, ensuring alignment with core values and requirements.

Driven by Davis’s (1989) technology acceptance model (TAM) and Westaby’s (2005) behavioral reasoning theory (BRT), the purpose of this study is to develop and test a conceptual model and examine consumers’ acceptance of artificial intelligence (AI) chatbots for apparel shopping.

Data from 353 eligible US respondents was collected through a self-administered questionnaire distributed on Amazon Mechanical Turk, an online panel. Confirmatory factor analysis and path analysis were used to test all hypothesized relationships using the structural equation model.

The results show that optimism and relative advantage of “reasons for” dimensions have a positive and significant influence on perceived ease of use (PEU), while innovativeness and relative advantage have a positive and significant influence on perceived usefulness (PUF). Discomfort and insecurity have no significant impact on PEU and PUF. However, complexity has a negative and significant impact on PEU but not on PUF. Additionally, PEU has a positive influence on PUF. Both PEU and PUF have a positive and significant influence on consumers’ attitudes toward using AI chatbots, which, in turn, affects the intention to use AI chatbots for apparel shopping. Overall, this study identifies that optimism, innovativeness and relative advantage are enablers and good reasons to adopt AI chatbots. Complexity is a prohibitor, making it the only reason against adopting AI chatbots for apparel shopping.

This study contributes to the literature by integrating TAM and BRT to develop a research model to understand what “reasons for” and “reasons against” factors are enablers or prohibitors that significantly impact consumers’ attitude and intention to use AI chatbots for apparel shopping through PEU and PUF.