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To maximize the network total profit by calculating the difference between costs and revenue (first objective function). To maximize the positive impact on the environment by integrating GSCM factors in RL (second objective function). To calculate the efficiency of disassembly centers by SDEA method, which are selected as suppliers and maximize the total efficiency (third objective function). To evaluate the resources and total efficiency of the proposed model to facilitate the allocation resource process, to increase resource efficiency and to improve the efficiency of disassembly centers by Inverse DEA.

The design of a closed-loop logistics network for after-sales service for mobile phones and digital cameras has been developed by the mixed-integer linear programming method (MILP). Development of MILP method has been performed by simultaneously considering three main objectives including: total network profit, green supply chain factors (environmental sustainability) and maximizing the efficiency of disassembly centers. The proposed model of study is a six-level, multi-objective, single-period and multi-product that focuses on electrical waste. The efficiency of product return centers is calculated by SDEA method and the most efficient centers are selected.

The results of using the model in a case mining showed that, due to the use of green factors in network design, environmental pollution and undesirable disposal of some electronic waste were reduced. Also, with the reduction of waste disposal, valuable materials entered the market cycle and the network profit increased.

(1) Design a closed-loop reverse logistics network for after-sales services; (2) Introduce a multi-objective multi-echelon mixed integer linear programming model; (3) Sensitivity analysis use Inverse-DEA method to increase the efficiency of inefficient units; (4) Use the GSC factors and DEA method in reverse logistics network.

The present study uses a meta-analysis technique to explore the association between corporate governance and dividend policy. The extant literature delivers inconclusive findings on the relationship between corporate governance and dividend policy. Therefore, this study aims to resolve the issues and deliver comprehensive results.

The study involves a meta-analysis of 53 research studies using preferred reporting items for systematic reviews and meta-analyses and population, intervention, comparison, outcome and study design approaches. The paper examines the impact of moderators: corporate governance structure (Anglo-American, communitarian or emerging system) and dividend distribution metrics (dividend over net income, dividend over total assets and absolute amount of dividend/dividend per share). The study involves subgroup analysis and meta-regression analysis to examine the impact of moderators.

The study’s results specify that board size and percentage of female directors significantly impact the dividend decisions of the company. In addition, subgroup analysis and meta-regression results demonstrate that dividend measurement proxy moderates the association between corporate governance and dividend policy.

Based on the existing literature surveyed, to the best of the authors’ knowledge, the current study is the first to conduct a meta-analysis on the relationship between corporate governance and dividend policy. This paper is unique and the first one of its kind (to the best of the authors’ knowledge) to cover all these moderating variables under an umbrella and consolidate the results to understand the existing knowledge and direct future research in the area of corporate governance and dividend decisions.

This study examines the moderating effects of cultural distance and the nationality of foreign subsidiaries’ CEOs on the relationship between internal/external network tie strength and technological innovation. This study focuses on foreign subsidiaries of Korean firms operating in emerging markets, based on the knowledge-based view.

To test the hypotheses, a survey was administered to 3,840 foreign subsidiaries of Korean firms in emerging markets. Questionnaires were distributed via phone and email, and 282 (7.34%) completed questionnaires were returned. Accordingly, an empirical analysis was conducted, and the hypotheses were tested.

First, internal network tie strength had a significant negative effect on foreign subsidiaries’ technological innovation. Second, external network tie strength had a significant positive effect on foreign subsidiaries’ technological innovation. Third, as for the moderating effect, cultural distance negatively moderates the significant negative effect of internal network tie strength on the technological innovation of foreign subsidiaries. Fourth, cultural distance positively moderates the positive effect of external network tie strength on foreign subsidiaries’ technological innovation. Fifth, foreign subsidiaries’ CEO nationality (parent country nationals) positively moderates the negative effect of internal network tie strength on foreign subsidiaries’ technological innovations. Sixth, foreign subsidiaries’ CEO nationality (parent country nationals) negatively moderates the positive effect of external network tie strength on foreign subsidiaries’ technological innovation.

Previous studies found a positive relationship between dual network tie strength and technological innovation in foreign subsidiaries from a knowledge-based view. This study’s significance lies in its finding that the varying strengths of foreign subsidiaries’ internal and external network connections can have different impacts on their technological innovation in the context of subsidiaries operating in emerging markets. Additionally, the moderating effects of cultural distance and the nationality of the foreign subsidiary’s CEO were examined. Therefore, this study is significant because it expands the literature on technological innovation in foreign subsidiaries.

This paper aims to offer an integrated framework for branded apps (BAs) that highlights research gaps and points to areas for future research.

Using a systematic literature review approach, the authors analyzed more than 100 articles published between 2009 and the present. This research used databases such as SCOPUS, Web of Science, EBSCO and Elsevier’s Science Direct, with a particular focus on articles listed in the 2021 ABS index. The reviewed papers were coded and organized into four categories in terms of themes and concepts: antecedents, mechanisms, outcomes and moderators.

The study identified four types of antecedents (app benefits, personal traits, brand benefits and others) that influence outcomes via cognitive, affective and a mix of both mechanisms, which is termed multipaths. The authors classified outcomes into five areas (financial gains; app benefits; brand benefits; customer benefits; and others). Moderators were grouped into four types (customer individuality; app features; brand characteristics; and others). The authors concluded by recommending promising directions for future research. Specifically, the authors suggested an inverted U-shaped relationship between escapism and customer responses to BAs.

This paper focused exclusively on BAs, differentiating them from other mobile apps. The authors integrated nearly 100+ studies conducted over two decades. This integrated model serves as a guiding tool for understanding the past, present and future of BAs.

Lean Six Sigma (LSS) implementation follows a structured approach called define-measure-analyze-improve-control (DMAIC). Earlier research about its application in emergency healthcare services shows that it requires organizational transformation, which many healthcare setups find difficult. The Kotter change management model facilitates organizational transformation but has not been attempted in LSS settings till now. This study aims to integrate the LSS framework with the Kotter change management model to come up with an integrated framework that will facilitate LSS deployment in emergency health services.

Two-stage Delphi method was conducted by using a literature review. First, the success factors and barriers of LSS are investigated, especially from an emergency healthcare point of view. The features and benefits of Kotter's change management models are then reviewed. Subsequently, they are integrated to form a framework specific to LSS deployment in an emergency healthcare set-up. The elements of this framework are analyzed using expert opinion ratings. A new framework for LSS deployment in emergency healthcare has been developed, which can prevent failures due to challenges faced by organizations in overcoming resistance to changes.

The eight steps of the Kotter model such as establishing a sense of urgency, forming a powerful guiding coalition, creating a vision, communicating the vision, empowering others to act on the vision, planning for and creating short-term wins, consolidating improvements and producing still more change, institutionalizing new approaches are derived from the eight common errors that managers make while implementing change in the institution. The study integrated LSS principles and Kotter’s change management model to apply in emergency care units in order to reduce waste and raise the level of service quality provided by healthcare companies.

The present study could contribute knowledge to the literature by providing a framework to integrate lean management and Kotter's change management model for the emergency care unit of the healthcare organization. This framework guides decision-makers and organizations as proper strategies are required for applying lean management practices in any system.

The proposed framework is unique and no other study has prescribed any integrated framework for LSS implementation in emergency healthcare that overcomes resistance to change.

Building on technology acceptance and learning transfer theories, this study aims to evaluate the integration of mobile augmented reality (MAR) in omnichannel retailing touchpoints for Generation Z (or Gen Z)'s apparel shopping, assessing how habitual augmented reality (AR) use in nonretailing contexts impacts Gen Z's motivations, acceptance and use of MAR shopping apps.

A total of 562 participants downloaded a footwear MAR app and completed a survey. Data were analyzed using confirmatory factor analysis and multivariate regression to explore moderated mediation effects.

The study reveals a paradigm shift: Gen Z's habitual use of AR in social media (e.g. Snapchat and TikTok face filters) significantly influences their intent to use MAR in shopping, overshadowing hedonic motivations. This marks a transition from AR as a gimmick to a practical utility in omnichannel touchpoints, with performance expectancy emerging as a critical mediator in adopting MAR for utilitarian purposes.

This study highlights how Gen Z consumers’ tech habits influence their pragmatic view of MAR, urging re-exploration of the main constructs of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model.

Findings suggest Gen Z values practicality over fun in MAR shopping apps, guiding marketers to emphasize tangible benefits for this demographic.

This research underscores the evolving perception of AR in retail among mobile natives, highlighting the shift from novelty to habitual utility. It offers strategic insights for integrating AR into omnichannel strategies, catering to the utilitarian expectations of Gen Z in the digital retail landscape.

The primary objective of this study is to conduct a comprehensive literature review focused on the concept of service quality within the healthcare sector. This research aims to categorize and analyze the various dimensions associated with service quality.

The systematic literature review methodology was employed to accomplish current study goals, and specific criteria were utilized to select relevant research articles spanning the years from 2000 to 2023. Ultimately, 57 articles met the criteria and were included in the study.

Through a meticulous review of selected articles, our research identified and categorized 29 distinct measures for evaluating service quality in the healthcare sector. These measures were further grouped into five overarching categories, namely: overall service quality, personal characteristics, healthcare facility administration, patient attributes and the servicescape. Our investigation highlighted that the dimensions commonly utilized to assess service quality in healthcare primarily draw from the SERVQUAL framework. Additionally, there is significant emphasis on measurements related to the physical environment's quality, overall patient satisfaction and behavioral intention.

This review offers original value by synthesizing diverse literature on healthcare service quality, highlighting SEVQUAL dimensions and critical variables used for assessment. It provides insight into the subjective nature of service quality and varied sampling methods and contributes to enhancing service quality and patient satisfaction in healthcare settings.

This paper aims to explore the barriers and facilitators to psychosocial well-being among ethnic Nepali Bhutanese American older adults from the perspective of health care and service providers working with this population. Specifically, the authors aimed to understand health-care and service providers’ perceptions of the psychosocial well-being in this community and appropriate interventions.

Qualitative research methods were used to collect and analyze data in collaboration with a community-based organization. A total of ten participants were interviewed. Interviews were conducted in either English or Nepali, based on participant preference. An inductive thematic analysis approach was used to analyze the data.

Three major themes were generated from the analysis. The first two were in reference to perceived barriers to mental well-being among Bhutanese American older adults: isolation that older adults faced in the USA and shifting responsibilities and lifestyles that arose from the cultural and structural barriers in the USA. Throughout these themes, there was an understanding that acculturation threatened families’ connections to each other and impacted older adults’ connections with younger generations. The third theme, a perceived facilitator of well-being, was the power of storytelling to counteract feelings of isolation and disempowerment caused by shifting lifestyles felt by older adults, especially amid community events.

Bhutanese American older adults, many of whom have limited English proficiency, face numerous challenges, psychosocial stressors and factors contributing to well-being. Care for this population should prioritize dignity, empowerment and the incorporation of strengths within their narratives. Interventions and services tailored for older Bhutanese American adults need to be adapted to integrate multiple care systems.

Highlights in academic papers serve as condensed summaries of the author’s key work, allowing readers to quickly grasp the paper’s focus. However, many journals do not currently offer highlights for their articles. To address this gap, some scholars have explored using supervised learning methods to extract highlights from academic papers. A significant challenge in this approach is the need for substantial amounts of training data.

This study examines the effectiveness of prompt-based learning for generating highlights. We develop task-specific prompt templates, populate them with paper abstracts and use them as input for language models. We employ both locally inferable pre-trained models, such as GPT-2 and T5, and the ChatGPT model accessed via API.

By evaluating the model’s performance across three datasets, we find that the ChatGPT model performed comparably to traditional supervised learning methods, even in the absence of training samples. Introducing a small number of training samples further enhanced the model’s performance. We also investigate the impact of prompt template content on model performance, revealing that ChatGPT’s effectiveness on specific tasks is highly contingent on the information embedded in the prompts.

This study advances the field of automatic highlights generation by pioneering the application of prompt learning. We employ several mainstream pre-trained language models, including the widely used ChatGPT, to facilitate text generation. A key advantage of our method is its ability to generate highlights without the need for training on domain-specific corpora, thereby broadening its applicability.