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This paper aims to prioritize the most efficient Six Sigma project that can generate the greatest benefit to the organization, according to the relative performance among a set of homogenous projects (in here, DMUs). The selection of a Six Sigma project is a multiple-criteria decision-making problem, which is difficult in practice because the projects are not yet complete and the values of evaluation indicators are often interval or imprecise data. Managers stress the need for developing an effective performance evaluation methodology for selecting a Six Sigma project.

This study proposes a modified model considering interval or imprecise data based on common weight data envelopment analysis (DEA) approach to solve problems on project selection.

By comparing its findings with an example from a previous study, the new model obtained realistic and fair evaluation results and significantly reduced the difficulties and the time spent during calculation. Moreover, not only the best project is identified, but also the exact indicator information is obtained.

This study solves the problem of selecting the most efficient Six Sigma project in the preference of interval or imprecise data. Many studies have shown how a Six Sigma project is chosen, but only a few have integrated interval data into the selection process.

Metadata are fundamental in establishing a digital library and museum while domain communities describe, interpret and manage different digital objects. Although many metadata formats and sets have been developed, it is difficult to choose an appropriate format and conversion is problematical, especially for the Chinese materials. This paper is a progress report from the Metadata Taskforce Group designing Chinese metadata for the digital library and museum project (DLMP) at Academia Sinica in Taiwan. The group’s top priority is to construct goals, principles and procedures while designing the metadata format for Chinese contents. Not only does the Metadata Taskforce Group present the analysis of content attributes of Formosan Plain indigenous people, but also several marked achievements and findings are suggested, such as the metadata record structure and criteria of selecting and evaluating the current metadata formats.

This study aims to reveal the influencing factors of user churn behavior and explore how these factors influence user churn behavior of rural public digital cultural services (RPDCS), and then, to provide the avoidance strategies for user churn behavior of RPDCS.

Combined with the stimulus–organism–response theory and cognitive load theory, this study constructed a mixed model of user churn behavior. Data collected through online and offline questionnaire survey were tested using the partial least squares structural equation modeling approach, and finally, the authors proposed a user churn behavior model of RPDCS.

The results indicate that the environmental stimulus factors of RPDCS affected user churn behavior via user organism factors. This study suggests that administrators should pay more attention to the information demand of users and strengthen the effective supply of RPDCS. Meanwhile, it is necessary to improve the information literacy of rural users to restrain the user churn behavior and improve the effectiveness of RPDCS.

The research findings on the influencing factors of user churn behavior shed light on the user churn behavior in public digital cultural services, add new knowledge to the construction of the public cultural services system and provide empirical evidence for how to improve the utilization and effectiveness of RPDCS.

This study aims to explore the relationship between elderly users' trust in public digital cultural services (PDCS) and their intention to use PDCS, and reveal the factors affecting their intentions from the perspective of trust to make recommendations that will increase their intention to use PDCS.

Combined with the trust building model and social exchange theory, this study constructed a conceptual model of elderly users' intention to use PDCS. Data collected from Chinese elderly users who have reached the age of 60 through questionnaire surveys were tested using the structural equation model with partial least squares. Finally, the authors proposed a model of elderly users' intention to use PDCS.

This study finds that elderly users' trust positively affects their intention to use PDCS from two aspects: service features and user features of PDCS. Concerning the service features, system quality directly affects elderly users' trust in PDCS most significantly, followed by information quality and service reputation. Concerning the user features, perceived value has a higher impact on elderly users' trust than that of service features, and information literacy and information quality directly affect perceived value.

This study adds new knowledge to the users' behavior of PDCS and enriches the prior description of PDCS. The recommendations made in this study provide a series of strategies for practitioners and researchers to improve the elderly users' intention to use PDCS and bridge the silver digital divide, which offers new ideas for improving the efficiency of PDCS.

The hospitality industry has recently witnessed explosive growth in robotization with the replacement of robots in many areas. Yet, a key consideration in this robotics wave is whether competition (i.e. robots take over all human tasks) or collaboration (i.e. humans collaborate closely with robots to perform work better) will define the future of the hospitality workspace. The purpose of this paper is to shed light on this controversial issue by taking a collaborative perspective to address the future human–robot relationship in hospitality workplace (i.e. cobotic team).

Drawing upon relevant theories and extant robotics literature, this paper will develop a critical reflection on the management of future cobotic team as a new phenomenon in hospitality industry.

The successful management of cobotics in hospitality lies in three interrelated key domains: feeling intelligence training for frontline employees, ethics governance for cobotics and trust building toward robot partners.

How to manage this cobotic team efficiently will be a focus for hospitality managers in the coming years. This paper offers several managerial insights for hospitality managers and practitioners regarding effectively managing the future collaboration between humans and robots within a dynamic work environment.

This study addresses cobotics as a critical yet unaddressed shift in the contemporary hospitality sector and proposes a framework highlighting three key domains for managing this cobotic team effectively. This framework also sets the direction to encourage more future empirical research exploring cobotic workforce in hospitality.

The user churn (UC) of rural public digital cultural services (RPDCS) indicates that rural users no longer use RPDCS or have switched to other services. The purpose of this study is to investigate the factors influencing RPDCS's UC and to contribute toward bridging the rural digital divide.

Based on the stimulus-organism-response theory, this study proposes a theoretical framework to investigate the factors influencing RPDCS's user churn. A total of 120 RPDCS users were initially recruited and 90 representative participants were chosen. Data were collected from the 90 respondents and 20 follow-up interviews. To examine the proposed framework and validate the correlations between these factors and UC, an analysis of variance (ANOVA) and multiple regression analysis were used. In addition, recommendations are made to avoid the UC of RPDCS to bridge the rural digital divide.

The results indicate that the UC of RPDCS was stimulated by both physical and ability divides and RPDCS ineffectiveness, resulting in increased churn rates and an exacerbated digital divide. Thus, avoiding the UC of RPDCS is an important way to bridge the rural digital divide, which includes both the physical and ability divides.

This study adds new knowledge about RPDCS and distinguishes it from previous research on public digital cultural services. In addition, the authors discuss how to avoid the UC of RPDCS, to bridge the rural digital divide.

This research aims to grasp hotel guests' motives and potential benefits sought when interacting with other guests, service personnel and residents and examines how these benefits can contribute to the total guest experience.

Mixed methods are adopted for the purpose of this study comprising individual interviews and a questionnaire survey.

Five groups of advantages emerge from individual interviews, including friendliness in interaction, social benefits, information acquisition, curiosity gratification and hospitality services. In the survey, which gathers 326 questionnaires, this study reveals that the five types of benefits derived from hotel guests' interactions could be further categorized into two dimensions: civility (e.g. friendliness and social) and utility (e.g. information, curiosity and service). The study confirms that four out of five potential or expected benefits from this personal interaction is significantly associated with the total hotel experience.

Respondents of this study are culturally homogenous; as a result, multi-cultural settings should be considered for future research.

Tourism and hospitality literature on people's interaction is mostly center around social aspects of interaction. The current study comprehensively explores all expected utilities of interaction, occurring in all sorts of interactions (e.g. customer-to-resident and customer-to-service personnel). Specifically, the findings of this study uncover the underlying factors which prompt the tourists to interact with other people in a lodging setting and examine the relative importance of those underlying factors to the total lodging experiences.

The purpose of this paper is to evaluate design performance of 51 gear shaping machines by using data envelopment analysis (DEA).

Existing studies extend traditional DEA by handling bounded and discrete data based on envelopment models. However, value judgment is usually neglected and fail to be incorporated in these envelopment models. In many cases, there is a need for prior preferences. Using existing DEA approaches as a backdrop, the current paper presents a methodology for incorporating assurance region (AR) restrictions into DEA with bounded and discrete data, i.e. the assurance region bounded discrete (AR-BD) DEA model. Then, the AR-BD DEA model is combined with a context-dependent DEA to obtain an efficiency stratification.

The authors examine different AR restrictions and calculate efficiency scores of five scenarios of AR restrictions by using the proposed AR-BD DEA model. It shows that AR restrictions have a great impact on the efficiency scores. The authors also identify nine efficient frontiers in total. For each decision-making unit, it could set benchmarks and improve its performance based on each higher efficient frontier.

This paper first evaluates efficiency of gear shaping machines by considering different (bounded and discrete) variable types of data and including AR restrictions. The AR-BD DEA model and context-dependent AR-BD DEA model proposed in this paper further enrich the DEA theory. The findings in this paper certainly provide useful information for both producers and consumers to make smart decisions.

This paper aims to investigate emerging trends in data analytics and knowledge management (KM) job market by using the knowledge, skills and abilities (KSA) framework. The findings from the study provide insights into curriculum development and academic program design.

This study traced and retrieved job ads on LinkedIn to understand how data analytics and KM interplay in terms of job functions, knowledge, skills and abilities required for jobs, as well as career progression. Conducting content analysis using text analytics and multiple correspondence analysis, this paper extends the framework of KSA proposed by Cegielski and Jones‐Farmer to the field of data analytics and KM.

Using content analysis, the study analyzes the requisite KSA that connect analytics to KM from the job demand perspective. While Kruskal–Wallis tests assist in examining the relationships between different types of KSA and company’s characteristics, multiple correspondence analysis (MCA) aids in reducing dimensions and representing the KSA data points in two-dimensional space to identify potential associations between levels of categorical variables. The results from the Kruskal–Wallis tests indicate a significant relationship between job experience levels and KSA. The MCA diagrams illustrate key distinctions between hard and soft skills in data across different experience levels.

The practical implications of the study are two-fold. First, the extended KSA framework can guide KM professionals with their career planning toward data analytics. Second, the findings can inform academic institutions with regard to broadening and refining their data analytics or KM curricula.

This paper is one of the first studies to investigate the connection between data analytics and KM from the job demand perspective. It contributes to the ongoing discussion and provides insights into curriculum development and academic program design.

The research objectives were to: (1) examine the relationship among motivations, satisfaction and loyalty with plant-based food dining at destinations; (2) determine if and how the attractiveness of eating plant-based foods moderates satisfaction and loyalty; and (3) investigate potential differences in visitor background information and consumption characteristics.

A survey was conducted at tourist attractions in southern Taiwan and 274 valid questionnaires were obtained. The relationships among motivations, satisfaction and loyalty were investigated when eating plant-based foods during travel. The moderating effects of food attractiveness on motivations and satisfaction/loyalty were measured.

The results indicated a positive relationship between motivations and satisfaction/loyalty in plant-based food dining. Motivations for plant-based food dining were comprised of four domains (physical, cultural, interpersonal and prestige) and satisfaction and loyalty had three (overall satisfaction, intention to revisit and intention to recommend).

The major implications were that motivations had a significant effect on satisfaction and loyalty; food attractiveness did not moderate the effect of motivations on satisfaction/loyalty; and background characteristics influenced satisfaction and loyalty.

Marketers and strategic planners for plant-based restaurants or those with plant-based meal options must make a greater effort to understand the distinctive demographic and dietary characteristics of the people who comprise the core of this market.

This research adds to the very limited literature on plant-based and vegetarian dining in tourism destinations. Furthermore, it tests, partially validates and expands a model by Kim et al. (2009) for consuming local food while traveling. The findings also complement the considerable evidence linking motivations to satisfaction and loyalty when dining.