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In today’s rapidly evolving work landscape, the design of office spaces is a crucial concern for organizations. Companies are redefining offices as collaboration hubs to entice employees back to in-person work. However, the understanding of how employees choose their workspaces, especially for collaborative activities, and how this should inform office design is lacking. Workers’ collaborative activity patterns can help better understand workspace choice behavior (WCB). In two studies, this paper aims to explore which characteristics of collaborative activities to consider when reshaping offices.

Data collected in a cross-sectional study design at a research institution (n = 285) and a university (n = 352) were used for confirmatory factor analyses and regression analysis.

The first study shows that collaborative activities can be classified into three distinct types: coordinative activities (planned and formal), deep collaboration (planned and complex) and spontaneous communication (informal and short encounters). The second study revalidates this classification and reveals patterns impacting WCB. Frequency and location preference of spontaneous communication and work environment satisfaction are strong predictors of on-site work. Personal characteristics like gender, age, managerial position or commute time are less consequential than assumed.

The results pinpoint guidelines for office designers and leaders in shaping effective workspaces and policies.

This paper provides new insights into classifying collaborative activities and personal characteristics, activity characteristics and environmental factors influencing WCB.

The primary objective of this investigation was to explore how employees’ utilization of social media for work-related purposes impacts their service innovation behavior, both directly and through the intermediary mechanisms of knowledge management and employees’ risk-taking.

In developing its conceptual framework, this study has drawn upon the stimulus-organism-response (SOR) theory. To test its hypotheses, this study has surveyed 241 financial analysts from ten Iranian financial companies and has employed variance-based structural equation modeling (specifically, PLS-SEM) with the assistance of “WarpPLS 8.0 software.”

The findings revealed that employees’ work-related use of social media positively influences their service innovation behavior using knowledge management, encompassing knowledge sharing and acquisition capability as well as employee risk-taking. However, this influence is not directly significant.

To the best of our knowledge, this study marks the first instance in which the effect of work-related use of social media on employee service innovation behavior directly and through the mediating roles of knowledge management and risk-taking has been investigated through the lens of the SOR paradigm, especially in the financial sector.

This study aims to evaluate Artificial Intelligence (AI) research in the hospitality industry based on the service AI framework (mechanical-thinking-feeling) and highlight prospective avenues for future inquiry in this growing domain.

This paper conceptualizes timely concepts supported by research spanning multiple domains.

This research introduces a novel classification for the domain of AI hospitality research. This classification encompasses prediction and pattern recognition, computer vision, NLP, behavioral research, and synthetic data generation. Based on this classification, this study identifies and elaborates upon five emerging research topics, each linked to a corresponding set of research questions. These focal points encompass the realms of interpretable AI, controllable AI, AI ethics, collaborative AI, and synthetic data generation.

This viewpoint provides a foundational framework and a directional compass for future research in AI within the hospitality industry. It pushes the industry forward with a balanced approach to leveraging AI to augment human potential and enrich customer experiences. Both the classification and the research agenda would contribute to the body of knowledge that will guide the industry toward a future where technology and human service coalesce to create unparalleled value for all stakeholders.

In recent years, much has been discussed about new consumer practices based on the sharing economy. In this context, the purpose of this paper is to map out the international scientific production on sharing economy.

The research adopted a descriptive qualitative approach. Based on a sample of 95 documents collected in the Scopus database, analyses of bibliometric and sociometric indicators were carried out, as well as content analyses were conducted to identify the main thematic categories in the field.

The results show that sharing economy is an emerging topic, and of late, the research in this field has grown rapidly. The study provides a mapping of top journals and authors, works of greatest impact and of co-authorship, co-citation and bibliographic coupling networks, which evidence the low intensity of researcher’s interactions and scientific production dispersion in the field. The main subjects found in the sharing economy literature are determinants, motivations and barriers, sharing economy impacts, regulation, models and frameworks, critical approach and entrepreneurship and sharing-based new businesses.

The analyses did not take into account the timing perspective. Further research could undertake a timeline-based approach in order to present direct citation networks and to relate works according to the year when they were published.

The study innovates by identifying the main subjects in the sharing economy literature, as well as by presenting network analysis for some bibliometric indicators, complementing previous research in the field.

This paper focuses on knowledge sharing in health care. The aim of the paper is to further understand how digital applications can facilitate knowledge sharing between different care providers and health-care professionals.

The paper is based on a qualitative action case study, performed as a formative intervention study as a Change Laboratory, where a digital application concerning wound support was used. The Change Laboratory was used for knowledge sharing in the assessment and treatment process of wounds. The collected data was then thematically analyzed.

The findings show how digital applications can facilitate knowledge sharing, but also the need for complementary collaborative sessions. The main contribution is the rich description of how digital applications together with these sessions can facilitate knowledge sharing.

This paper shows that activities as collaborative sessions performed on the organizational level prove to support knowledge sharing and learning when a new digital application has been implemented in the work process. It also shows that these sessions contributed to identifying new knowledge that has potential for being included in the application and hence are important to keeping the application updated and relevant over time.

This review article is focused on the following research questions: RQ1: What are the methods used by authors to collect data in order to evaluate one's profile? RQ2: What are the classification algorithms and ranking metrics used to give suggestions to users? RQ3: How effective are these algorithms and metrics identified in RQ2?

There are four major systematic review phases being carried out in this survey, namely the formulation of research questions, conducting the review, which includes the selection of articles and appraising evidence quality, data extraction and narrative data synthesis.

Collecting from primary sources is more personalized and relevant. Embedded skill sets that have a considerable impact on one’s career aspirations could be mined from secondary sources. A hybrid recommender system helped mitigate the limitations of both. The effectiveness of the models depends not only rely on the filtering techniques used but also on the metrics used to measure similarity and the frequency of words or phrases used in a document.

The study benefits internship program coordinators of a university aiming to develop a recommender or matching system platform for their students. The content of the study may shed a light on how university decision-makers can explore options on what are the techniques or algorithms to be integrated. One of the advantages of internship or industrial training programs is that they would help students align them with their career goals. Research studies have discussed other RS filtering techniques apart from the three major filtering techniques.

The outcome of the study, which is a recommendation system to match a student's profile with the knowledge and skills being sought by organizations, may help ease the challenges encountered by both parties. The study benefits internship coordinators of a university who are planning to create a recommendation system, an innovative project to be used in teaching and learning.

Internship programs can help a student grow personally and professionally. A university student looking for internship opportunities can find it a daunting task to undertake, as there is a vast pool of opportunities offered in the market. The confidence levels needed to match their knowledge, skills and career goals with the job descriptions (JDs) could be challenging. The same holds with companies, as finding the right people for the right job is a tough endeavor. The main objective of conducting this study is to identify models implemented in recommendation systems to give and/or rank suggestions given to users.

While surveys regarding recommender systems (RS) exist, there are gaps in the presentation of various data collection methods and the comparison of recommendation filtering techniques used for both primary and secondary sources of data. Most recommendation systems for internship programs are intended for European universities and not much for Southeast Asia. There are also a limited number of comparative studies or systematic review articles related to recommendation systems for internship programs offered in an Southeast Asian landscape. Systematic reviews on the usability of the proposed recommendation systems are also limited. The study presents reviews of articles, from data collection and techniques used to the usability of the proposed recommendation systems, which were presented in the articles being studied.

This study aims to facilitate consistency of information in building information modelling (BIM) and address the current BIM gaps through the perspectives of the productization concept and product structure (PS).

The study follows a conceptual research approach in conjunction with a single case study. First, the previous studies on BIM implementation, productization and PS are reviewed. Further, a case study is used to analyse the current state of productization in the construction sector and develop a functional PS for construction.

A Part-Phase-Elements Matrix is proposed as a construction-specific PS to facilitate consistency in information and to enhance BIM. The proposed matrix provides new avenues to facilitate consistent information exchange through the interconnection between conceptual PS and standard building objects library, and encourage collaborative communication between stakeholders.

This study explores the core of the productization concept and PS as means to facilitate consistency of information and thus address the current gaps in BIM. This as building projects progressively move towards systematic modular and prefabricated construction where the flow of reliable information about product and construction offerings becomes increasingly important.

This paper aims to share the experience of a collaborative platform for social innovation (SI) in urban governance in Brussels (Belgium) and to formulate recommendations for future initiatives.

The publicly funded collaborative platform “Brussels by us”, which aimed to improve the quality of life in specific neighbourhoods in Brussels (Belgium), is presented as a case study for SI in urban governance. The case study is detailed according to four dimensions based on the SI and living lab literature.

While the initiative appeared to be a successful exploration platform for collaborative urban governance, it did not evolve into concrete experimentation nor implementation of the solutions. Possible explanations and recommendations are formulated.

The findings of this paper are based on the experience of a one-year initiative. The results should be completed by similar case studies of longitudinal initiatives, and with other levels of implementation such as experimentation and concrete implementation of solutions.

This paper presents a concrete case study of a collaborative platform implemented in a specific neighbourhood in Brussels (Belgium). Its digital and offline approach can help other practitioners, scholars and public institutions to experiment with the living lab methodology for the co-ideation of solution in urban governance. The four-dimensional framework presented in the study can provide future initiatives with a structured reporting and analysis framework, unifying and strengthening know-how in the domain of SI.

The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution.

The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments.

Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes.

The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept.

The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application.

This paper aims to investigate the ways in which “non-collaborative co-creation” can affect brand equity as perceived by independent observers. It reports a study of the different effects on that perception attributable to non-collaborative co-creation that takes the form of either “brand play” or “brand attack” and is executed either by established artists or mainstream consumers.

A 2 × 2 between-subjects experiment (brand play versus brand attack; consumer versus artist) measured observers’ perception of brand equity before and after exposure to purpose-designed co-created treatments.

Non-collaborative co-creation has a negative effect on observers’ perceptions of brand equity and brand attack, causing a stronger dilution of brand equity than brand play. Artists either mitigate the dilution or have a positive effect on those perceptions.

Future research could usefully investigate the relative susceptibility of brands to non-collaborative co-creation, the effects on brands of higher complexity than those in our experiment, exposed in higher-involvement media, and the effects of more diverse forms of co-creation.

Brand managers must recognise that co-creation carries considerable risks for brand equity. They should closely monitor and track the first signs of non-collaborative co-creation in progress. It could be beneficial to recruit artists as co-creators of controlled brand play.

This study offers a more complete insight into the effect of non-collaborative co-creation on observers’ perceptions of brand equity than so far offered by the existing literature. It connects the fields of brand management and the arts by investigating the role and impact of artists as collaborative or non-collaborative co-creators of brand equity.