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The main purpose of this paper is to outline the antecedents of patient satisfaction in the field of medical tourism (MT) applying extant literature and to develop a conceptual model based on the review.

This paper presents a thorough review of prior studies related to the antecedents of patient satisfaction in the MT sector. Moreover, it provides the theoretical base that helped the researcher to identify significant relationship between the patient satisfaction and its antecedents.

The researchers identified the prominent antecedents of patient satisfaction and present the potential interrelationships between different antecedents of patient satisfaction such as treatment quality, cost attractiveness, destination image and service quality with patient satisfaction based on the review.

The results have momentous practical implications as they will help researchers to better understand the antecedents of patient satisfaction and their potential inter linkages with patient satisfaction in MT sector. The conceptual model derived from the review may guide the actions of researchers as well as practitioners in the MT industry as a whole. The present study provides insights for further research in the MT sector and thereby helps to further enrich the existing theoretical base of the MT.

The study brings together the scattered knowledge from the broad and extensive range of medical or health tourism and cognate literature which indicate ideological differences among various aspects of MT as well as potential factors determining patient satisfaction in MT sector (antecedents of satisfaction). The newly developed model incorporates a new construct called “treatment quality” as different from “service quality,” which is a widely used construct to explain customer satisfaction. The antecedents of patient satisfaction and their inter-linkages with patient satisfaction provide a sound theoretical foundation for the future studies.

Measuring the diffusion of protests, or more generally, the diffusion of events, is an ongoing task in social sciences. This paper proposes an inter-event approach to study what types of protests tend to diffuse or decline. We develop a standardized, five-step procedure to measure what we define as “event diffusion momentum” (EDM): (1) employ event-based data containing information on the time, location, and features of each protest; (2) define the temporal and spatial ranges of interest; (3) for each observation, count the number of events before and after it within the defined ranges; (4) predict the numbers of post-event and pre-event protests with appropriate count models; (5) calculate the ratios of predicted values for each predictor and confidence intervals using the delta method. The ratio is the EDM. Applying this method to Dynamics of Collective Action (DoCA) data, we identify several micro- and macro-level factors associated with protest diffusion in the United States, 1960–1995. We conclude with the implications and generalizability of the proposed method.

This research aimed to explore individuals with intellectual disabilities (ID) experiences of the therapeutic relationship.

Six individuals with ID were recruited who were currently having 1:1 therapy. Semi-structured interviews focused on their experiences of the therapeutic relationship.

Using interpretative phenomenological analysis, six personal experiential themes were identified. These were labelled as a person-centred experience, the importance of adaptions, “I feel like I know you”, a secure base is offered, change does occur and an overlap of subjective experience. The results indicate that participants’ accounts of their experiences indicated that the relationship was important to them. This research also demonstrated that the benefits and value of involving individuals with ID in qualitative research.

To the best of the authors’ knowledge, exploring the therapeutic relationship from the perspective of individuals with ID has not been previously explored in the literature. This research highlights considerations for therapists working with this population to help them facilitate positive therapeutic outcomes.

The purpose of this paper was to investigate what types of supply chain strategies (SCS) are implemented within luxury fashion companies, according to the drivers that regulate competitiveness in this sector (brand positioning, distribution channel, type and line of product). Moreover, the objective was to define which key performance indicators (KPIs) should be measured according to the chosen strategy, and finally to evaluate the alignment of luxury fashion companies with the proposed indicators.

The literature review was the first step performed. Thereafter, a case study was conducted and the sample, composed of six companies, was selected, a questionnaire was then developed to guide the interviews, after which the data were collected. From the data, a primary case analysis was conducted, from which cross-case patterns were also researched.

From the results obtained, it was possible to state that companies involved in the case study adopted different SCS within the same company according to the drivers that regulate the sector competitiveness. As a result, the product line was shown to be the only driver that affected both the alignment between the expected and implemented SCS, respectively, and the alignment with the selected KPIs.

The paper provides valuable insights to companies that are trying to align SCS and KPIs. The close link between these aspects had not yet been explored previously. In particular, there were no indications about the KPIs that have to be measured for a specific SCS.

This study aims to investigate the effects of interaction in agricultural product live rooms, including personalization, responsiveness, and entertainment, on consumers’ purchase intention.

The SOR model has been applied to formulate hypotheses. This study is based on an online survey conducted with a sample of 433 valid questionnaires from Chinese consumers on the TikTok agricultural products live platform. A partial least squares structural equation modeling (PLS-SEM) is used to test the hypotheses.

The findings indicate that (1) interactions (personalization, responsiveness, and entertainment) in the agricultural products live room have a positive effect on perceived values (utilitarian value, symbolic value, and entertainment value); (2) utilitarian value positively affects purchase intention and mediates the effects of personalization and entertainment interactions on purchase intention, respectively; (3) entertainment value positively influences purchase intention and mediates the influence of entertainment interaction on purchase intention.

This study offers theoretical insights into live marketing of agricultural products and practical implications for practitioners of agricultural products in live streaming commerce.

This paper aims to investigate Supply Chain (SC) Performance Measurement Systems (PMSs) (SCPMSs) that are suitable and applicable to evaluate SC performance during unexpected events such as global pandemics. Furthermore, the contribution of Industry 4.0 Disruptive Technologies (IDTs) to implement SCPMSs during such Black Swan events is investigated in this study.

The research methodology is based upon a novel qualitative and quantitative mixed-method. A Systematic Literature Review (SLR) was initially employed to identify two complete lists of SCPMSs and IDTs. Then, a novel Interval-Valued Intuitionistic Hesitant-Fuzzy (IVIHF)-Delphi method was firstly developed in this paper to screen the extracted SCPMSs. Afterward, the Propriety, Economic, Acceptable, Resource, Legal (PEARL) indicator of the Hanlon method was innovatively applied to prioritize the identified IDTs for each finalized SCPMS.

Two high-score SCPMSs including the SC operations reference (SCOR) model and sustainable SCPMS were recommended to improve measuring the performance of the pharmaceutical SC of emerging economies such as Iran in which the societal, biological and economic issues were undeniable, particularly during unexpected events. Employing nine IDTs such as simulation, big data analytics, cloud technologies, etc., would facilitate implementing sustainable SCPMS from distinct perspectives.

This is one of the first papers to provide in-depth insights into determining the priority of contribution of IDTs in applying different SCPMSs during global pandemics. Proposing a novel multi-layer mixed-methodology involving SLR, IVIHF-Delphi, and the PEARL indicator of the Hanlon method is another originality offered by this paper.

This study explores how factors arising from supply chain (SC) network and complexity work together in supply chain learning (SCL) behavior.

Fuzzy set qualitative comparative analysis, which is an emerging configurational analysis method, was adopted to examine the complex combination of five influencing factors. The data were collected using a two-stage survey. First, the authors selected seven typical firms with an awareness of SCL. Second, questionnaires were sent to the partners of the seven selected firms, and 156 valid questionnaires were obtained from 76 firms.

Drawing on emergent insights from the initiative, the authors find that multiple configurations of SC network and complexity lead to high SCL. Specifically, weak ties are necessary conditions of such learning, while strong ties are also conducive to this. Moreover, a moderate SC complexity is conducive to SCL.

This study enriches the understanding of SCL and provides new insights for SC management practitioners to take measures to improve it.

This study addresses the lack of in-depth understanding of the antecedent conditions of SCL in the literature. It establishes an integrated and comprehensive theoretical framework of such learning based on contingency theory. Additionally, this study incorporates ambidextrous SCL (i.e. creation capability and dispersion capacity). An overall prototype of SCL capability is proposed on SC network and complexity theory.

This paper aims to examine how Airbnb has been transformed from an informal form of tourism accommodation into an emerging form of tourism e-micro-entrepreneurship through an interesting triangle consisting of three distinct parts: hosts, platform and guests.

Considering that the peer-to-peer response has sealed the sharing economy's success, research methodology involves primary research that focuses on the adeptness of Airbnb hosts as e-micro-entrepreneurs from the customers' perspective. A quantitative methodology was employed by applying a convenience sampling strategy through a structured questionnaire that was distributed online, resulting in a collection of 150 useable responses. A statistical analysis has been performed to test the research's objectives.

Driven by Airbnb hosts' entrepreneurial behavior in managing their listings and guests' responses, research findings led to the development of a post-conceptual IRMA model, which describes this particular form of hosting as an e-micro-entrepreneurship opportunity, while guests' satisfaction confirms the platform's performance and hosts' efforts in service quality provision.

This study brings valuable insights to the tourism e-entrepreneurship literature through the assessment of the Airbnb platform and the hosts as e-micro-entrepreneurs, providing useful information to researchers and managers involved in the Sharing Economy's disruptive innovation and a more complete understanding of the drivers of Airbnb's consumer adoption.

Research on Airbnb mainly focuses on service quality from the customer perspective, while the existing literature does not highlight how a new type of e-micro-entrepreneurship has emerged by operating in the sharing economy's disruptive innovation ecosystem, which illustrates the factors that motivate hosts and guests to share accommodation services in an equilibrium bond.