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The article investigates the institutional setup of e-lending in public libraries in Denmark, Norway and Sweden. Our point of departure is that e-lending has necessitated new library collaborations between local, regional and national levels, and therefore, institutional e-lending setups have emerged. The study seeks to provide better understanding of how the institutional setups are structured, how governance logics have shaped them and what tensions and dynamics become visible in the key actors’ problematisations of these setups.

The study is situated in the neo-institutional tradition and applies the institutional logics perspective. The research questions are answered by taking a qualitative approach, grounded in an extensive interview study with representatives of libraries, publishers and policy actors in three Scandinavian countries. To provide in-depth insight into e-lending setups, the scope of empirical material is then limited to accounts the central library and policy actors involved in establishing e-lending.

The analysis shows that the e-lending setups are both similar (especially when it comes to financing), and different across Scandinavia, especially when it comes to centralisation and involvement of librarians in this task. The differences are attributed to the influence of different governance logics (question of administrative autonomy, collaboration in the field and existing legal and political frames), and to what extent the digital and market logics are incorporated or rejected in the field.

The study provides new insights into the question of how Scandinavian public libraries face the consequences of the digitalisation of book distribution and consumption by investigating how they organise their e-lending services. This has not been explored before, notably in a comparative perspective.

The main objectives of the current study are to assess the existing situation of historical city centers in Iran and to offer prioritized appropriate regeneration strategies for their sustainable development.

The study is based on a questionnaire-based survey in four historical city centers of Iran: Kashan, Naeen, Ardakan and Yazd. The required data have been collected using multiple tools including questionnaires and interviews with local residents and officials in the aforementioned case studies. Using the strengths, weaknesses, opportunities and threats (SWOT) technique, a set of appropriate strategies for the sustainable regeneration of these valuable fabrics has been proposed and the best of them have been prioritized employing quantitative strategic planning matrix (QSPM) matrix.

The results show that the current situation in all the case studies is not in line with sustainability and cultural heritage protection. Their multiple problems are mostly associated with their weaknesses, whilst their strengths, including a considerable potential as a tourism attraction, are scarcely exploited. The experts and residents surveyed for this research have provided basic information to establish the conservative strategies that should take priority when preparing the urban regeneration process of these areas.

Since most of the adopted regeneration strategies in Iran are not supported by empirical studies, the current study largely fulfills this shortcoming by setting up a proper diagnosis of historical city centers in Iran and proposes the most appropriate regeneration strategies based on the findings.

This paper investigates the impact of family influence measured by the F-PEC scale on private enterprise (both family firms and lone founders) leadership succession strategy.

The research dataset is comprised of 390 private enterprises whose head offices were situated in the voivodeships of Lower Silesia and Wielkopolska in Poland. The authors collected data through CAPI (computer-assisted personal interviewing) method, as well as through comprehensive, structured interviews with company owners. Data were analysed using hierarchical logistic regression for each type of succession strategy.

The results suggest that increased family influence does not necessarily lead to intra-family leadership succession in private enterprises. Importantly, a range of findings contradicted authors' predictions. The relationship between the overall F-PEC scale values signifying the multi-faceted family influence over the business and the choice of internal successor was weakly negative for the total sample; also, the higher the overlap between family and business values and the higher the commitment to family business, as evidenced by the Culture subscale, the lower was the occurrence of intra-family successor choice in the population of lone founders. The Culture subscale also increased the prevalence of lack of succession planning in the sample of lone founders.

While several studies suggests that family firms may be more prone to choose an intra-family succession scenario, it remains unclear how lower levels of business and succession experience, may influence the successor choice. Indeed, some studies suggest that a strong family influence over a business, may stimulate family firms to choose a family outsider as a business leader. Therefore, the key contribution of this study is contextualizing the response to an ongoing succession debate. This study investigates the strategic choices of companies in the first generation of ownership operating in Poland, which serves as an example of a post-transition economy. While the characteristics of this economic environment may be unique, the authors discuss how the surprising findings may add to the understanding of the general succession processes present in private enterprises.

Sourcing decisions are one of the most crucial strategic decisions in companies and often confronted with inherent unexpected uncertainties and risks. This study aims to investigate the impact of ownership involvement on purchasing (PUR) supplier selection activities, including risk consideration in family firms (FFs).

The investigation is based on a structured literature review (SLR) of 83 studies to identify FF-specific supplier sourcing characteristics. To verify these propositions, the authors conducted a second SLR of non-FF behaviour research (179 papers) to generate a non-FF reference base for the respective behavioural characteristics. Following this analysis, the authors conducted 16 qualitative and explorative-oriented expert interviews (EIs).

Based on reviews, the authors deduce that PUR activities of family and non-FFs are different regarding the PUR decision processes and PUR risk behaviour, and that suppliers' selection criteria like sustainability, partnership and long-term orientation are prioritised in FFs. Additionally, several trends of family and non-FF behaviour approximation were identified. Besides these findings, it might be expected that the differentiating characteristics of family and non-FFs vary based on their region or industry sector. The EIs indicated that “the depth of added values” should be considered as a further potential differentiating influence factor.

The analysis encourages to execute further quantitative studies on FF sourcing activities and requests managers to strengthen the position of the PUR departments in FFs.

Established in 2010, Mellower Coffee has 40 exquisite chain stores and three branches, namely Mellower Coffee Sales, Mellower Business Management and Shanghai Mellower Roasting Factory. Positioned as a premium coffee brand in China, Mellower Coffee has realized the integrated operation and management of the whole industrial chain from raw coffee trade, roasting factory, coffee retail products, specialty coffee chain, office coffee to coffee academy. It has a vision to attract and cultivate more and more coffee lovers by constant innovation coffee culture promotion.

This study attempts to examine the relationship between reliable big and cloud data analytics capabilities (RB&CDACs) and comparative advantages (CA) of manufacturing firms (MFs) in the Middle East region as developing countries using green product innovation (GPI) and green process innovations (GPrI) mediating factors, further assess the role of data-driven competitive sustainability factor as a moderated factor.

436 useable online surveys were analyzed using the quantitative approach for the data-gathering process, applying structural equation modeling in the Smart-PLS program as an analysis tool. The sample unit for analysis included all middle- and senior-level managers and employees within MFs. The authors performed convergent validity and discriminant validity tests, bootstrapping also was applied. The authors included GPI and GPrI as mediating factors while using data-driven competitive sustainability as a moderated factor.

The findings of this study indicated that there is a positive significant effect in the relationship between reliable big and cloud data analytics capabilities and comparative advantages, which is supported by the formulated hypothesis. Furthermore, the findings confirmed that there was a positive and significant effect through the mediating factors (i.e. GPI and GPrI) on comparative advantage, additionally, it confirmed and supported that the moderating factor represented by data-driven competitive advantage suitability has significant effect as well.

This study has some limitations represented by using only one type of methodological approach (i.e. quantitative), further, it was conducted on only Asian countries in the Middle East region.

This piece of work improved the proposed conceptual research model and included several factors such as reliable big and cloud data analytics capabilities, comparative advantage, data-driven competitive sustainability, GPI and GPrI. This research offered new and valuable information and findings for managers, practitioners and decision-makers in the MFs in the Middle East region as a road map and gaudiness for the importance to apply these factors in their firms for enhancing the comparative advantages in their firms. Further, this research fills the gap in SCM literature and makes a bridge of knowledge and contribution to the existence of previous studies.

As the role of senior school leaders has become more complex, the leadership of improvement, innovation and change has been distributed to middle leaders. However, middle leaders are often not prepared for the shift to strategic thinking and leading. This chapter provides an overview of what it means to think and lead strategically when leading from the middle. Then, the theory is translated into practical templates and tools that can be employed by a middle leader. The context of this chapter is leading a faculty in a secondary school; however, the ideas and examples provided are easily translated to any middle leading context.

This study examines the mediating roles of the three dimensions of business intelligence (sensing capability, transforming capability and driving capability) in the relationship between the three dimensions of big data analytics capability (big data analytics management, technology and talent capabilities), and radical innovation among Chinese manufacturing enterprises.

A theoretical framework was developed using the resource-based view. The hypothesis was tested using empirical survey data from 326 Chinese manufacturing enterprises.

Empirical results show that, in the Chinese manufacturing context, business intelligence sensing capability, business intelligence transforming capability and business intelligence driving capability positively mediate the impact of big data analytics capability on radical innovation.

The results offer managerial guidance for leaders to properly use big data analytics capability, business intelligence and radical innovation as well as offering theoretical insight for future research in the manufacturing industry’s radical innovation.

This is among the first studies to examine three dimensions of big data analytics capability on the manufacturing industry’s radical innovation by considering the mediating role of three dimensions of business intelligence.

Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention approach to handling innovation-induced conflicts that may hinder smooth implementation of big data technology in project teams.

This study uses constructs from conflict theory, and team power relations to develop an explanatory framework. The study proceeded to formulate theoretical hypotheses from task-conflict, process-conflict, relationship and team power conflict. The hypotheses were tested using Partial Least Square Structural Equation Model (PLS-SEM) to understand key preventive measures that can encourage conflict prevention in project teams when implementing big data technology.

Results from the structural model validated six out of seven theoretical hypotheses and identified Relationship Conflict Prevention as the most important factor for promoting smooth implementation of Big Data Analytics technology in project teams. This is followed by power-conflict prevention, prevention of task disputes and prevention of Process conflicts respectively. Results also show that relationship and power conflicts interact on the one hand, while task and relationship conflict prevention also interact on the other hand, thus, suggesting the prevention of one of the conflicts could minimise the outbreak of the other.

The study has been conducted within the context of big data adoption in a project-based work environment and the need to prevent innovation-induced conflicts in teams. Similarly, the research participants examined are stakeholders within UK projected-based organisations.

The study urges organisations wishing to embrace big data innovation to evolve a multipronged approach for facilitating smooth implementation through prevention of conflicts among project frontlines. This study urges organisations to anticipate both subtle and overt frictions that can undermine relationships and team dynamics, effective task performance, derail processes and create unhealthy rivalry that undermines cooperation and collaboration in the team.

The study also addresses the uncertainty and disruption that big data technology presents to employees in teams and explore conflict prevention measure which can be used to mitigate such in project teams.

The study proposes a Structural Model for establishing conflict prevention strategies in project teams through a multidimensional framework that combines constructs like team power conflict, process, relationship and task conflicts; to encourage Big Data implementation.