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In the African context, the threat of the disruption of traditional business value-creation processes, currently facilitated by the growing information technology (IT) ecosystem, came with the coronavirus disease 2019 (COVID-19) pandemic. Thus, this paper aims to investigate the impacts of the COVID-19 pandemic on interfirm relationships within the context of the digital ecosystem in Africa.

This study employs an explanatory–exploratory qualitative approach from an interpretivist stance to investigate the impacts of the COVID-19 pandemic on interfirm relationships. The authors conducted seven in-depth interviews with top management executives in a Nigerian technology company, together with the company's archival data that provided the pre, during and post pandemic (2018–2021) business-to-business (B2B) relationship structures, to determine how these relationships have been affected.

The results suggest that the pandemic had a minimal effect on partnership relationships in the B2B ecosystems of the case company but affected only non-partnership relationships.

The authors' qualitative study is interpretive and the sample size is limited. Hence, there is a need for caution in generalizing the findings. The framework can be further validated across a wider population.

Partnerships can help organizations weather business crises. Consequently, organizations should maintain a healthy number of partnership relations to deal with periods in which challenges emerge in the business landscape. In other words, with tight contracts and a strategic focus on goals and objectives, partnership relations can help organizations weather business crises.

This study builds upon the burgeoning body of literature on digital ecosystems within the African context, which is a relevant contextual contribution.

This study aims to explore how and why self-discrepancy affects materialism and impulsive buying and the extent to which subjective well-being mediates the relationship between self-discrepancy, materialism and impulsive buying.

The authors have tested the hypothesis with a convenience sample (N = 434) from Lithuania. Descriptive analysis, principal components analysis (PCA), serial mediation hypothesis tested with model 81 from regression-based path analysis modeling tool PROCESS Macro for IBM® SPSS® Statistics 24.7 statistical software.

The serial and parallel mediation analysis results indicated that greater self-discrepancy was related to poorer life satisfaction, which was related to greater materialism centrality, which promoted greater impulsive buying. Also, the greater the self-discrepancy, caused more occurrence of negative affect, which relates to increased materialism happiness, which triggers impulsive buying. Self-discrepancy was negatively associated with the frequency of positive affect, which was positively related to materialism, which stimulates impulsive buying.

The study was dominated by younger respondents. The survey was conducted during the lockdown of the Covid-19 virus pandemic.

There is little empirical evidence to support the reasoning behind why self-discrepancy predicts a higher degree of materialism, which increases impulsive buying. This study suggests the mechanism of how subjective well-being affects relationships of self-discrepancy on materialism and impulsive buying.

There has been a huge fluctuation in online marketplace that suggests inconsistencies of m-commerce usage. The study investigates user behaviour to continued patronage of m-commerce and the mediating role of perceived value.

The study aimed to use adapted questionnaire and online version to pool data from respondents that has internet profile and conducts m-commerce. The hypotheses were proven through the use of structural equation model.

In this paper performance expectancy and user satisfaction are major determinants of continuance intention to use m-commerce in African context while perceived value partially mediate the relationship between the variables.

Cross-sectional survey and the small sample size that was used calls for caution in generalisation.

With the mediating influence of perceived value, attention is directed to the role of value perception of m-commerce users. Keeping and increasing continuance usage requires pleasurable offerings and value indices that influence their subjective perceptions.

The significance of the mediating variable highlights the social value dimension of users' value perception given that it can help to deepen the continuous usage of m-commerce.

The predictive power of 78.5% continuance intention demonstrates inclusion of factors with better predictive accuracy. Importantly, the significance of perceived value as a mediator demonstrates the importance of valuing not only the direct impacts of the variables but also the indirect roles that impacts continuance intention of m-commerce in African context.

Mining user-concerned actionable and interpretable hot topics will help management departments fully grasp the latest events and make timely decisions. Existing topic models primarily integrate word embedding and matrix decomposition, which only generates keyword-based hot topics with weak interpretability, making it difficult to meet the specific needs of users. Mining phrase-based hot topics with syntactic dependency structure have been proven to model structure information effectively. A key challenge lies in the effective integration of the above information into the hot topic mining process.

This paper proposes the nonnegative matrix factorization (NMF)-based hot topic mining method, semantics syntax-assisted hot topic model (SSAHM), which combines semantic association and syntactic dependency structure. First, a semantic–syntactic component association matrix is constructed. Then, the matrix is used as a constraint condition to be incorporated into the block coordinate descent (BCD)-based matrix decomposition process. Finally, a hot topic information-driven phrase extraction algorithm is applied to describe hot topics.

The efficacy of the developed model is demonstrated on two real-world datasets, and the effects of dependency structure information on different topics are compared. The qualitative examples further explain the application of the method in real scenarios.

Most prior research focuses on keyword-based hot topics. Thus, the literature is advanced by mining phrase-based hot topics with syntactic dependency structure, which can effectively analyze the semantics. The development of syntactic dependency structure considering the combination of word order and part-of-speech (POS) is a step forward as word order, and POS are only separately utilized in the prior literature. Ignoring this synergy may miss important information, such as grammatical structure coherence and logical relations between syntactic components.

Companies utilize increasingly capable Artificial Intelligence (AI) technologies to deliver modern services across a range of consumer service industries. AI autonomy, however, sparks skepticism among consumers leading to a decrease in their willingness to adopt AI services. This raises the question as to whether consumer trust in companies can overcome consumer reluctance in their decisions to adopt high (vs low) autonomy AI services.

Using a representative survey (N = 503 consumers corresponding to N = 3,690 observations), this article investigated the link between consumer trust in a company and consumers' intentions to adopt high (vs low) autonomy AI services from the company across 23 consumer service companies accounting for six distinct service industries.

The results confirm a significant and positive relationship between consumer trust in a company and consumers' intentions to adopt AI services from the same company. AI autonomy, however, moderates this relationship, such that high (vs low) AI autonomy weakens the positive link between trust in a company and AI service adoption. This finding replicates across all 23 companies and the associated six industries and is robust to the inclusion of several theoretically important control variables.

The current research contributes to the recent stream of AI research by drawing attention to the interplay between trust in companies and adoption of high autonomy AI services, with implications for the successful deployment and marketing of AI services.

This study aims to present a state-of-the-art review of building information modelling (BIM) in the Swedish construction practice with a focus on wood construction. It focuses on examining the extent, maturity and actual practices of BIM in the Swedish wood construction industry, by analysing practitioners’ perspectives on the current state of BIM and its perceived benefits.

A qualitative approach was selected, given the study’s exploratory character. Initially, an extensive review was undertaken to examine the current state of BIM utilisation and its associated advantages within the construction industry. Subsequently, empirical data were acquired through semi-structured interviews featuring open-ended questions, aimed at comprehensively assessing the prevailing extent of BIM integration within the Swedish wood construction sector.

The research concluded that the wood construction industry in Sweden is shifting towards BIM on different levels, where in some cases, the level of implementation is still modest. It should be emphasised that the wood construction industry in Sweden is not realising the full potential of BIM. The industry is still using a combination of BIM and traditional methods, thus, limiting the benefits that full BIM implementation could offer the industry.

This study provided empirical evidence on the current perceptions and state of practice of the Swedish wood construction industry regarding BIM maturity.

As the coronavirus disease 2019 (COVID-19) continues to spread across countries, it is becoming increasingly clear that the presence of pre-existing noncommunicable diseases (NCDs) dramatically increases the risk of aggravation in persons who contract the virus. The neglect in managing NCDs during emergencies may result in fatal consequences for individuals living with comorbidities. This paper aims to highlight the need for a paradigm shift in the governance of public health emergencies to simultaneously address NCD and noncommunicable disease (CD) pandemics while taking into account the needs of high-risk populations, underlying etiological factors, and the social, economic, and environmental determinants that are relevant for both CDs and NCDs.

The paper reviews the available global frameworks for pandemic preparedness to highlight the governance challenges of addressing the dual agenda of NCDs and CDs during a public health emergency. It proposes key strategies to strengthen multilevel governance in support of countries to better prepare for public health emergencies through the engagement of a wide range of stakeholders across sectors.

Addressing both CD and NCD pandemics during public health emergencies requires (1) a new framework that unites the narratives and overcomes service and system fragmentations; (2) a multisectoral and multistakeholder governance mechanism empowered and resourced to include stakeholders across sectors and (3) a prioritized research agenda to understand the political economy of pandemics, the role played by different political systems and actors and implementation challenges, and to identify combined strategies to address the converging agendas of CDs and NCDs.

The article is based on the review of available published evidence.

The uptake of the strategies proposed will better prepare countries to respond to NCD and CD pandemics during public health emergencies.

The article is the first of its kind addressing the governance challenges of the dual pandemic of NCDs and CDs in emergencies.

This study aims to develop the understanding of learning processes related to the new ways of interacting in the enforced digital workplace over time.

A multiple, longitudinal case study of knowledge-based workers in three firms located in Sweden has been conducted from March 2020 to March 2023. In total, 89 interviews with 32 employees in three knowledge-based firms have been collected.

The study shows how the intricate interaction between rules and norms for interaction and work must be renegotiated as well as un- and relearned when the physical work environment no longer frames the work context. Furthermore, technology can be viewed as both an enable and a barrier, that is, technology has enhanced collaboration between organizational members yet also created social difficulties, for example, related to communication and interaction. The study emphasizes that individuals learned through trial and error. That is, they tried behaviors such as translating social interactions" to a digital arena, appraised the outcomes and modified the practices if the outcomes were poor.

The present study does have several limitations. First, it is based on interviews with respondents within three organizations in Sweden. To broaden and deepen the understanding of both organizational and learning, future studies can contribute by studying other contexts as well as using a mixed method approach in other countries.

Results from the study can provide a practical understanding of how the rapid change from working at the office to working from home using digital technologies can be understood and managed.

Contributions include combining interaction order and un- and relearning among organizational employees. This insight is important given that the rapid digital transformation of our society has changed how work is performed and how the future workplace will be both structured and organized.

The main purpose of this study is to make a comparative evaluation of the impacts of previous outbreaks and coronavirus disease 2019 (COVID-19) on the tourism industry. COVID-19 appears to have disrupted all memorizations about epidemics ever seen. Nobody has anticipated that the outbreak in late December will spread rapidly across the world, be fatal and turn the world economy upside down. Severe acute respiratory syndrome, Ebola, Middle East respiratory syndrome and others caused limited losses in a limited geography, thus similar behaviors were expected at first in COVID-19. But it was not so. Today, people continue to lose their lives and experience economic difficulties. One of the most important distressed industries is undoubtedly tourism.

This study is a literature review. In this review, a comparative evaluation between the impact of previous outbreaks and COVID-19 on the tourism industry has been made based on statistics and previous research studies.

The information and figures obtained show that COVID-19 and previous outbreaks have such significant differences that cannot be compared. COVID-19 has been one of the worst to live in terms of spreading speed, the geography where it spreads, loss of lives and negative effects in the whole area.

It is noteworthy that COVID-19 is very severe in terms of death cases and also its impacts on the economy compared to other pandemics. It remains to be argued that COVID-19 can also be a reference in terms of possible new outbreaks in the future, and is an effective actor in determining future strategies.

This study aims to review the literature on sharing economy logistics and crowd logistics to answer the three following questions: How is the literature on sharing economy logistics structured? What are the main trends in sharing economy logistics and crowd logistics? What are the future research options?

Bibliometric analysis is used to evaluate 85 articles published over the past 12 years; it identifies the top academic journals, authors and research topics contributing to the field.

The sharing economy logistics and crowd logistics literature is structured around several disciplines and highlights that some are more scientifically advanced than others in their subject definitions, designs, modelling and innovative solutions. The main trends are organized around three clusters: Cluster 1 refers to the optimal allocation of costs, prices, distribution and supplier relationships; Cluster 2 corresponds to business related crowdsourcing and international industry practices; and Cluster 3 includes the impact of transport on last-mile delivery, crowd shipping and the environment.

The study is based on data from peer-reviewed scientific journals and conferences. A broader overview could include other data sources such as books, book chapters, working papers, etc.

Future research directions are discussed in the context of the evolution from crowd logistics to crowd intelligence, and the complexities of crowd logistics such as understanding how the social crowd can be integrated into the logistics process. Our results are part of the crowd science and engineering concept and provide some answers about crowd cyber-system questions regarding crowd intelligence in logistic sector.