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We explore the simultaneous influence of activist organizations and corporations on institutional change. Focusing on protests, campaign contributions, and lobbyists as the strategies used by activist organizations and corporations to influence institutional change, we study the dynamics between movements and counter-movements and their influence on the probability of institutional change. In the context of the US tobacco industry, the results shed light on the effectiveness of these strategies and uncover potential moderators of this relationship. Overall, we demonstrate the simultaneous and asymmetric effects of activist organizations and corporations that use conspicuous and inconspicuous strategies to change institutions.

In the hybrid knowledge-sharing platform where paid and nonpaid (“free”) knowledge activities coexist, users’ free knowledge contribution may be influenced by financial factors. From the perspective of opportunity cost, this study investigates the direct effect of how the amount of monetary income from users’ contribution to paid knowledge activities influences their free knowledge contribution behavior in the future. Further, this study aims to verify the interaction effect of financial and nonfinancial factors (i.e. the experience of free knowledge contribution and social recognition) on free knowledge contribution.

Objective data was collected from a hybrid knowledge-sharing platform in China and then analyzed by using zero-inflated negative binomial regression model.

Results show that the amount of monetary income that knowledge suppliers gain from paid knowledge contribution negatively influences their free knowledge contribution. Experience of free knowledge contribution strengthens the negatively main effect, while social recognition has the weakening moderating role.

Although some studies have explored and verified the positive spillover effect of financial incentives on free knowledge contribution, the quantity dimension is ignored. This study examines the hindering influence of the quantity of monetary income from the perspective of opportunity cost. By taking the characteristic of knowledge suppliers and platforms as moderators, this study deepens the understanding of the influence of monetary income on free knowledge contribution in the hybrid knowledge-sharing platform.

The paper aims to investigate the link between models and system results. It looks at fundamental principles underlying social activities and strives to understand the logical role of models in social governing. Based on these a heuristic is assembled enabling the recognition of the specific contribution formal models can provide for social contexts and also for recognizing the limitations that apply.

The heuristic is developed based on first principles of systems theory and cybernetics with particular consideration of managerial cybernetics. It starts with the assumption that human cognition roots in an autopoietic process from which individual “realities” and Weltanschauungen evolve. Interaction then leads human actors to adopt social system notions through which they initiate and constantly reconcile the implementation of their commonly aspired purposes. With system structures, it is referred to how actors relate to each other in governing – which is a key to learning about what models can contribute. Therefore, the concept of system structure is derived from interaction and rooted in the social system notion distinguishing aspects of structural capacity that pre‐condition the implementation of desired social outcomes. Subsequently, a logical anatomy of system notions is revealed and expressed with a set of invariant systemic topics necessary when being addressed in governing.

The paper finds a heuristic for identifying the contribution formal models provide to the governance of social systems and recognition of the benefits and limitations specific models provide to governing. Conclusions are drawn on the pre‐conditions securing sustained organizational development through the application of formal models.

The heuristic assembled in this paper facilitates the harmonization and alignment of models in governance settings. The recognition of the role of models in social governing is identified as a logical pre‐condition of sustainable governance. The heuristic presented facilitates assessing and optimizing governing structures with respect to those pre‐conditions.

The purpose of this paper is to provide a customer lifetime value (CLV) model to carefully assess and classify banking customers using individual measures and covering customers’ relationships with a portfolio of products of the company.

The proposed model comprises two sub-models: (sub-model 1) modelling and prediction of CLV in a multiproduct context using Hierarchical Bayesian models as input to (sub-model 2) a value-based segmentation specially designed to manage customers and products using the latent class regression. The model is tested using real transaction data of 1,357 customers of a bank.

This research demonstrates which drivers of customer value better predict the contribution margin and product usage for each of the products considered in order to get the CLV measure. Using this measure, the model implements a value-based segmentation, which helps banks to facilitate the process of customer management.

Previous CLV models are mostly conceptual, generalisation is one of their main concerns, are usually focussed on single product categories using aggregated customer data, and they are not design with a special emphasis on their application as support for managerial decisions. In response to these drawbacks, the proposed model will enable decision makers to improve the understanding of the value of each customer and their behaviour towards different financial products.

Social loafing in knowledge contribution (namely, knowledge contribution loafing [KCL]) usually happens in group context, especially in the mobile collaboration tasks. KCL shows dynamic features over time. However, most previous studies are based on static assumption, that is, KCL will not change over time. This paper aims to reveal the dynamics of KCL in mobile collaboration and analyze how network centrality influences KCL states considering the current loafing state.

This study is based on empirical study design. Real mobile collaboration behavioral data related to knowledge contribution were collected to investigate the dynamic relationship between network centrality and KCL. In total, 4,127 chat contents were collected through Slack (a mobile collaboration APP). The text data were first analyzed using the text analysis method and then analyzed by a machine learning method called hidden Markov model.

First, the results reveal the inner structure of KCL, showing that it has three states (low, medium and high). Second, it is found that network centrality positively influences individuals involved in medium and high loafing state, while it has a negative influence on individuals with low loafing state.

The limitations are related to the single machine learning method and no subdivision of social network. First, this paper only uses one kind of text classification model (TF-IDF) to divide chat contents, which may not be superior to other classification models. This paper considers the eigenvector centrality, and not further divides the social network into advice network and expressive network.

This study helps companies infer tendency of different KCL and dynamically re-organize a mobile collaborative team for better knowledge contribution.

First, previous studies based on static assumptions regarding KCL as static and the relationship between loafing reducing mechanisms and team members KCL does not change over time. This study relaxes static assumptions and allows KCL to change during the process of collaboration. Second, this study allows the impact of network centrality to be different when members are in different KCL states.

This paper aims to consider a contribution model of a general Islamic insurance industry which allowed the return of underwriting profit to the Islamic insurance participants. The objective is to create a justified and equitable means of computing contribution which maximises the expected ownership right of the Islamic insurance fund.

The accumulation of funds and claims paid were characterised in form of accumulation and decay function over a period of time. It provides necessary and sufficient conditions for their existence and uniqueness. Mathematical derivative procedures were adopted to derive the underwriting returns to be returned to the Islamic insurance participants. Lastly, this paper recommends the incorporation of underwriting returns’ variable into the traditional actuarial model and provides theoretical justification for the process.

Then, the derivation of underwriting returns through convolution of accumulated funds and claims paid views in the form of Laplace Transform led to a conjecture and proved. Thereafter, the proposed and adjusted model was arrived at.

This study, to the best knowledge of the researcher, is the first attempt in the quantification of Islamic insurance industry. Thus, the model is the first attempt of creating a justified way of calculating the Islamic insurance participants’ contributions.

The purpose of this paper is to focus on conditional cooperation and investigate whether the difference in contributions between Partners and Strangers designs in linear public goods experiments can be explained by differences in beliefs.

The author conducted linear public goods experiments by using Partners and Strangers designs with belief eliciting their group member’s contributions.

The author shows that the difference in the magnitude of the responsiveness of contribution to belief (i.e. the marginal contribution to belief) creates different contribution levels in Partners and Strangers designs.

The presented results imply that having a strategic motive increases contributions by increasing the magnitude of the responsiveness of contribution to belief rather than by raising belief level.

The main claim of this paper is that “marginal contribution to belief” rather than “belief level” causes the difference in contribution levels between Partners and Strangers. This is the first proven evidence of a difference in belief between Partners and Strangers.

Business process management (BPM) has attracted much focus throughout the years, yet there have been calls questioning the future of BPM. The purpose of this paper is to explore the current state of the field through a dynamic literature review and identify the main challenges for its future development.

A dynamic co-citation network analysis identifies the “evolution” of knowledge of BPM and the most influential works. The results present the developed BPM subthemes in the form of clusters.

The focus within the field has shifted from facilitating wide-ranging business performance improvements to creating introverted optimizations within a particular BPM subgroup. The BPM field has thus experienced strong fragmentation throughout the years and has accrued into self-fueling subareas of BPM research such as business process modeling and workflow management. Those subareas often neglect related disciplines in other management, process modeling and organizational improvement fields.

The study is limited by the initial keyword choice of the authors. The subsequent co-citation analysis ameliorates the subjectivity since it produces a data set and contributions based on references.

A new combination of historical development and the state-of-the-art of the BPM field, by employing a co-citation and cluster analysis. This dynamic literature review presents the current state of the theoretical core and attempts to identify the crossroads that BPM has reached. The study can be replicated in the future to track the changes in the field.

The client‐supplier alignment problem is receiving growing attention in related literature and important contributions have been made for our understanding of the phenomenon. However, recent works agree on the fact that an integrative view of the problem is still lacking and consequently, a practical model is lacking also. The purpose of this paper is to present a new management control perspective that may help to improve understanding of the phenomenon.

From a review of the previous literature, the paper evolves into the conceptual development of a new model.

The paper argues that previous literature shows important limitations. First, its models try to find the best archetypes when evidence shows that no pure archetype can be found. Second, it has neglected the performance problem. Third, the suggested specific control mechanisms have been limited to the appropriation problem. In order to make a contribution, this paper presents an innovative and complete view of the client‐supplier alignment problem from a management control perspective that evolves into an integrative model which introduces the concepts of central misfit and management control paths.

The paper makes a contribution to the outsourcing literature by exposing previous biases and proposing an innovative view of the client‐supplier alignment problem. Moreover, the paper proposes a new model for the design of management control systems in order to improve performance. These contributions, although theoretical, could have a great practical impact as they could lead to a prescriptive model, useful for practitioners.

This research aims to select the best-fitting model(s) of equal risk contribution portfolios (ERC). ERC is a robust estimation in the absence of reasonable expectations about future returns.

The portfolio consists of five environmental-friendly exchange-traded funds (ETFs). It applies equal risk optimization, beneficial when the assets are firmly linked, such as the ETFs. This paper operationalizes 20 covariance models in portfolio construction, and a portfolio with classic covariance is the benchmark to beat. To select the best-fitting model(s), the paper applies statistical inferences of the model confidence set. This research also constructs the newly-developed minimum connectedness optimization method and utilizes maximum drawdown as the primary evaluation tool.

The outbreak of COVID-19 hugely impacts the portfolio drawdown. The results also show that the classic covariance is hard to beat, partly explained by estimation error and model misspecification. This paper suggests that equal risk contribution can benefit from copula-based covariance. It consistently and significantly outperforms the other models in various robustness tests.

In the absence of substantial predictions about future returns and the existence of strongly linked assets, selecting appropriate portfolio components by risk contribution is a sound choice.

This is the first paper to select the best-fitting model(s) of ERC portfolio during the COVID-19.