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This research aims to investigate the impact of missing visual information on tourists’ decision-making processes and visit intention. Drawing on perception completion law and signaling theory, the study hypothesized that tourists might use visual information to infer about a destination, even if the information is incomplete or ambiguous.

To assess the impact of missing visual information, the authors asked a group of 392 participants who had no prior familiarity with a specific garden museum to envision the interior environment of the museum garden and provide feedback on their emotional responses and aesthetic evaluations. To aid in their imagination, they were presented with a video showcasing the surrounding landscape and exterior of the museum.

The study found that participants could anticipate their overall experience of the location by inferring the resemblance of unseen areas to the images they had viewed, even without prior exposure or information. This study provides valuable insights into the cognitive processes underlying tourism decision-making and advances our understanding of how people form expectations of new and unfamiliar places.

The originality of this research relies on the mediating role of missing aesthetics and emotion on the relationship between available aesthetics and visit intention using a structural model. This study highlights the significant role of visual information in influencing tourist decision-making, even with incomplete or ambiguous data.

The author develops a bilateral Nash bargaining model under value uncertainty and private/asymmetric information, combining ideas from axiomatic and strategic bargaining theory. The solution to the model leads organically to a two-tier stochastic frontier (2TSF) setup with intra-error dependence. The author presents two different statistical specifications to estimate the model, one that accounts for regressor endogeneity using copulas, the other able to identify separately the bargaining power from the private information effects at the individual level. An empirical application using a matched employer–employee data set (MEEDS) from Zambia and a second using another one from Ghana showcase the applied potential of the approach.

This article compares the processes of community verification (CV) and user satisfaction surveys during the implementation of performance-based financing (PBF) in Mali and Burkina Faso.

The authors adopted a qualitative approach based on a multiple-case study design. Data were collected from August 10 to 25, 2017, in Mali, and from January to May 2016 in Burkina Faso. In Mali, 191 semi-structured interviews were conducted with investigators (people who collect information from health centre users in the communities, using survey tools), users, users' relatives, and health workers in three of the 10 health districts in the Koulikoro region. In Burkina Faso, 241 non-participatory observation sessions were recorded in a research diary, and 92 semi-structured interviews and informal discussions were conducted with investigators, community verifiers, users, PBF support staff at the national level, and administrative staff in one of the 15 health districts involved in PBF. The data were analysed inductively.

In both Mali and Burkina Faso, the delayed availability of survey forms led to a delay in starting the surveys. In Mali, to get off to a quick start, some investigators went to health centres to conduct the sampling with their supervisors. In both countries, investigators reported difficulties in finding certain users in the community due to incorrect spelling of names, lack of telephone details, incomplete information on the forms, common or similar sounding names within the community, and user mobility. There was little interference from health workers during user selection and surveys in both countries. In both countries, many surveys were conducted in the presence of the user's family (husband, father-in-law, brother, uncle, etc.) and the person accompanying the investigator. Also in both countries, some investigators filled in forms without investigating. They justified this data fabrication by the inadequate time available for the survey and the difficulty or impossibility of finding certain users. In both countries, the results were not communicated to health centre staff or users in either country.

CV and user satisfaction surveys are important components of PBF implementation. However, their implementation and evaluation remain complex. The instruments for CV and user satisfaction surveys for PBF need to be adapted and simplified to the local context. Emphasis should be placed on data analysis and the use of CV results.

There are similarities and differences in the CV process and user satisfaction surveys in Mali and Burkina Faso. In Mali, the data from the user satisfaction survey was not analyzed, while in Burkina Faso, the analysis did not allow for feedback. The local non-governmental organisations (NGOs) that carried out the CV were pre-financed for 50% of the amount in Mali. In Burkina Faso, community-based organisations (CBOs) were not pre-financed. The lack of financing negatively impacted the conduction of the surveys. In Mali, fraudulent completion of survey forms by interviewers was more common in urban than in rural areas. In Burkina Faso, the frauds concerned consultations for children under five years of age. In Burkina Faso, the survey form was not adapted to collect data on the level of satisfaction of the indigent.

1. There were similarities and differences in the community verification (CV) processes in Mali and Burkina Faso.

2. In both Mali and Burkina Faso, tracing users within their community was difficult for several reasons, including incorrect or incomplete information on forms, common or similar names, and user mobility.

3. In both countries, there was no feedback on the results of the CV process to health centre staff or users.

4. Survey forms were falsified by investigators in both countries. In Mali, falsification was more common in urban than in rural areas. In Burkina Faso, falsification was more often observed for consultations for children under five years of age.

There were similarities and differences in the community verification (CV) processes in Mali and Burkina Faso.

In both Mali and Burkina Faso, tracing users within their community was difficult for several reasons, including incorrect or incomplete information on forms, common or similar names, and user mobility.

In both countries, there was no feedback on the results of the CV process to health centre staff or users.

Survey forms were falsified by investigators in both countries. In Mali, falsification was more common in urban than in rural areas. In Burkina Faso, falsification was more often observed for consultations for children under five years of age.

We attempt to construct a grey three-way conflict analysis model with constraints to deal with correlated conflict problems with uncertain information.

In order to address these correlated conflict problems with uncertain information, considering the interactive influence and mutual restraints among agents and portraying their attitudes toward the conflict issues, we utilize grey numbers and three-way decisions to propose a grey three-way conflict analysis model with constraints. Firstly, based on the collected information, we introduced grey theory, calculated the degree of conflict between agents and then analyzed the conflict alliance based on the three-way decision theory. Finally, we designed a feedback mechanism to identify key agents and key conflict issues. A case verifies the effectiveness and practicability of the proposed model.

The results show that the proposed model can portray their attitudes toward conflict issues and effectively extract conflict-related information.

By employing this approach, we can provide the answers to Deja’s fundamental questions regarding Pawlak’s conflict analysis: “what are the underlying causes of conflict?” and “how can a viable consensus strategy be identified?”

This study aims to investigate the influence of customer satisfaction and brand loyalty on hotel guests’ repurchase intentions when they experience consumer confusion.

A quantitative research method was used in the study and the data were collected through a survey. A survey was used to collect data from 406 hotel guests staying at four and five-star hotels. The structural equation model was used to test the influence of consumer confusion on hotel guests’ repurchase intentions.

The findings of the study show that while consumer confusion has a negative effect on hotel guests’ repurchase intentions, customer satisfaction and brand loyalty have a positive influence on their repurchase intentions. Customer satisfaction and brand loyalty tend to have a partial mediating role in the relationship between consumer confusion and repurchase intention.

The findings show the need for the hotel management to provide simple, concise, yet sufficient information enabling tourists to differentiate their offerings to reduce confusion.

Previous research has largely neglected the role of guests’ loyalty and satisfaction with the hotel brand. This research shows that guests’ loyalty and satisfaction with the hotel brand play an important role in terms of the repurchase intention and in reducing confusion.

ChatGPT is a new development in this technological era. This artificial intelligence-based tool responds to individuals’ queries and produces the requested content within seconds. Therefore, it is becoming popular among academics, the research community and library professionals. This study aims to test (through personal interaction with the tool) the authenticity of the ChatGPT’s produced records. Another objective of the research is to check the relevance between the individuals’ queries and the tool’s results. The research also intends to identify the challenges in retrieving information through ChatGPT.

The five researchers from different countries and organizations experienced ChatGPT by asking questions on more than 70 subjects. The responses were recorded in Notepad and converted into MS Excel and MS Access to standardize and analyze the data. The investigators consulted 11 reputed databases/sources, including Web of Science and Scopus, to assess the authenticity of the data retrieved through ChatGPT.

The findings confirmed that over 90% of results produced by ChatGPT were fake (the information did not exist in the literature). Similarly, the study sheds light on the discrepancies, such as irrelevant and incomplete information in the data generated by ChatGPT.

This is a unique study that shares the findings based on the different regions’ researchers’ personal experiences with ChatGPT. The researchers covered different subject areas (above 70) while asking questions to ChatGPT. The paper shares implications for researchers, students, faculty members, academic/research organizations and policymakers.

It is largely acknowledged that arbitrating the flow of knowledge can help firms strategically leverage tacit and explicit internal knowledge. However, despite the apparent scholarly and managerial acceptance of the criticality of the flow of knowledge between various stakeholders, the academic understanding of knowledge arbitrage remains coarse-grained. There are practically no empirical insights available to unravel the consequences of firms’ knowledge arbitrage choices regarding rewards and risks. This study aims to identify the risks that emerge as firms channel the flow of knowledge from surplus to deficit areas within organizational boundaries. To this end, the authors investigate several subsumed subprocesses in knowledge arbitrage to map the associated risks.

This study used an exploratory qualitative approach to examine the risks that emerge as firms attempt to support knowledge flows within their organizational boundaries. The data were collected through open-ended essays via an online research platform from 45 full-time employees of firms operating in different sectors. The collected data were analyzed inductively through open, axial and selective coding.

The research findings identified three key subprocesses of knowledge arbitrage: knowledge diffusion, knowledge brokering and knowledge absorption. These subprocesses are susceptible to various risks arising the form of channels, champions, sharers and receivers of knowledge flows. In general, the study showed that a firm’s decision regarding knowledge flows, such as structured or random flows, or the presence or absence of designated coordinators to broker the flow carries specific risks for both sharers and receivers. In particular, while the risks of knowledge hiding, misinformation and disinformation manifest in all three subprocesses, low employee engagement, loss of knowledge and information overload also emerged as key risks in any two of the three subprocesses.

This study offers valuable insights by uncovering the hitherto unexplored risks in intrafirm knowledge arbitrage. Given that knowledge is a crucial organizational tool for driving performance, innovation and competitive advantage, understanding the risks associated with intrafirm arbitrated knowledge flows can help firms anticipate and mitigate the associated adverse consequences. The findings make a novel contribution by offering (a) a comprehensive categorization of the risks associated with knowledge arbitrage rooted in processes, people and structures and (b) a macro overview of knowledge arbitrage risks associated with the processes of knowledge diffusion, knowledge brokering and knowledge absorption.

Complex cost structures and multiple conflicting objectives make selecting an appropriate cloud service difficult. The purpose of this study is to propose a novel group consensus decision making method for cloud services selection with knowledge deficit by trust functions.

This article proposes a knowledge deficit-based multi-criteria group decision-making (MCGDM) method for cloud-service selection based on trust functions. Firstly, the concept of trust functions and a ranking method is developed to express the decision-making opinions. Secondly, a novel 3D normalized trust degree (NTD) is defined to measure the consensus levels. Thirdly, a knowledge deficit-based interactive consensus model is proposed for the inconsistent experts to modify their decision opinions. Finally, a real case study has been carried out to illustrate the framework and compare it with other methods.

The proposed method is practical and effective which is verified by the real case study. Knowledge deficit is an important concept in cloud service selection which is verified by the comparison of the proposed recommended mechanism based on KDD with the conventional recommended mechanism based on average value. A 3D NTD which considers three values (trust, not trust and knowledge deficit) is defined to measure the consensus levels. A knowledge deficit-based interactive consensus model is proposed to help decision-makers reach group consensus. The proposed group consensus model enables the inconsistent decision-makers to accept the revised opinions of those with less knowledge deficit, rather than accepting the recommended opinions averagely.

The proposed a knowledge deficit-based MCGDM cloud service selection method considers group consensus in cloud service selection. The concept of knowledge deficit is considered in modeling the group consensus measuring and reaching method.

The study aims to pioneer an innovative approach for the evaluation of government portal websites (GPWs) by introducing an eye-tracking-based method. The research meticulously pinpoints and analyses the distinct usability issues and challenges that users encounter while navigating and interacting with GPWs.

This study devises an eye-tracking-based GPW usability evaluation approach, which focuses on the major functions (i.e. government information disclosure, government services and interactive responses) of GPWs. An Entropy Weighted Technique for Order Preference by Similarity to an Ideal Solution (EW-TOPSIS) method is employed to process eye-tracking indicator results for deriving GPW usability results.

The proposed approach is demonstrated to assess the usability of 12 GPWs in pilot smart cities in China, and it is found that most GPWs have lower-than-average usability. GPWs with low usability require more cognitive load that exhibit increased fixation and saccade. The comparisons among the GPW usability results from (1) the eye-tracking experiment, (2) questionnaire surveys and (3) the ready-made performance evaluation report validate the effectiveness of eye-tracking-based GPW usability evaluation.

The work contributes to shifting the GPW usability evaluation approach from a subjective judgment paradigm to an objective paradigm, as well as provides implications for enhancing GPW usability, including improving search function, reducing website complexity and prioritizing user needs.

This study explores whether herd behavior exists for equity crowdfunding investors in China and whether this herding is rational.

Based on signaling theory and social learning theory, two hypotheses were proposed. This study employed two approaches to collect data. First, this paper analyzed 3,041 investments on an equity crowdfunding platform in China using Python programming and built a panel data model. Second, based on a unique experiment design, this study conducted several relevant herd behavior simulation experiments.

We found that investors in the Chinese equity crowdfunding market exhibit herd behavior and that this herding is rational. Project attributes play a negative role in moderating the relationship between the current investment amount and cumulative investments. Experimental results further support our findings.

This study contributes to the emerging literature on herding in crowdfunding by focusing on equity crowdfunding in China. We are the first to explore whether Chinese equity crowdfunding investors exhibit rational herding behavior. The study is also original in applying social learning theory to equity crowdfunding and in using both actual crowdfunding campaigns and experimental approaches to collect data. This study has valuable implications to practice.