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Patterns have proven to be useful for documenting general reusable solutions to a commonly occurring problem. In recent years, several different business process management (BPM)-related patterns have been published. Despite the large number of publications on this subject, there is no work that provides a comprehensive overview and categorization of the published business process model patterns. The purpose of this paper is to close this gap by providing a taxonomy of patterns as well as a classification of 89 research works.

The authors analyzed 280 research articles following a structured iterative procedure inspired by the method for taxonomy development from Nickerson et al. (2013). Using deductive and inductive reasoning processes embedded in concurrent as well as joint research activities, the authors created a taxonomy of patterns as well as a classification of 89 research works.

In general, the findings extend the current understanding of BPM patterns. The authors identify pattern categories that are highly populated with research works as well as categories that have received far less attention such as risk and security, the ecological perspective and process architecture. Further, the analysis shows that there is not yet an overarching pattern language for business process model patterns. The insights can be used as starting point for developing such a pattern language.

Up to now, no comprehensive pattern taxonomy and research classification exists. The taxonomy and classification are useful for searching pattern works which is also supported by an accompanying website complementing the work. In regard to future research and publications on patterns, the authors derive recommendations regarding the content and structure of pattern publications.

This paper addresses the social value of commercial enterprises that are jointly owned by a government and private sector investors and where the shares are listed on a stock exchange: thus, “listed public–private enterprises” (LPPEs). The theoretical part of the paper addresses how differences in ownership patterns influence the behavior and performance of LPPEs.

We develop a conceptual taxonomy, drawing on the empirical evidence on the behavior and performance of public–private hybrid enterprises and on the application of agency theory to that evidence. The taxonomy discussion predicts how different ownership patterns affect enterprise productive efficiency and the ability of governments to achieve social goals through LPPEs. We review the empirical literature on government enterprise ownership and on the concentration of private share ownership to deduce how these matter for owner and managerial behavior and productive efficiency. We review the literature that considers the informational content that listing of an enterprise's shares on a stock exchange can provide to enterprise owners, managers and other domestic audiences with a policy interest. We employ a social welfare perspective to derive policy implications as to when the LPPE governance structure is most appropriate.

We show how the monitoring and performance weaknesses of state ownership are offset by some private ownership, particularly when combined with listing on a stock exchange. We demonstrate the effects of different governance structures on enterprise productive efficiency. We find that the LPPE structure is particularly appropriate as an alternative to nationalization or to full privatization and regulation of natural monopoly public utilities, and as an alternative to full private ownership and taxation of non-renewable natural resource extractive enterprises.

This paper explicitly addresses the question of why and how the combination of government ownership, private investor ownership and listing on an exchange is socially valuable in providing information on productive efficiency to governments.

The aim of this paper is to present an online framework for building a domain taxonomy, called TaxoLine, from Web documents automatically.

TaxoLine proposes an innovative methodology that combines frequency and conditional mutual information to improve the quality of the domain taxonomy. The system also includes a set of mechanisms that improve the execution time needed to build the ontology.

The performance of the TaxoLine framework was applied to nine different financial corpora. The generated taxonomies are evaluated against a gold-standard ontology and are compared to state-of-the-art ontology learning methods.

The experimental results show that TaxoLine produces high precision and recall for both concept and relation extraction than well-known ontology learning algorithms. Furthermore, it also shows promising results in terms of execution time needed to build the domain taxonomy.

E-commerce companies use different types of dark patterns to manipulate choices and earn higher revenues. This study aims to evaluate and prioritize dark patterns used by e-commerce companies to determine which dark patterns are the most profitable and risky.

The analytic hierarchy process (AHP) prioritizes the observed categories of dark patterns based on the literature. Several corporate and academic specialists were consulted to create a comparison matrix to assess the elements of the detected dark pattern types.

Economic indicators are the most significant aspect of every business. Consequently, many companies use manipulative methods such as dark patterns to boost their revenue. The study revealed that the revenue generated by the types of dark patterns varies greatly. It was found that exigency, social proof, forced action and sneaking generate the highest revenues, whereas obstruction and misdirection create only marginal revenues for an e-commerce company.

The limitation of the AHP study is that the rating scale used in the analysis is conceptual. Consequentially, pairwise comparisons may induce bias in the results.

This paper suggests methodical and operational techniques to choose the priority of dark patterns to drive profits with minimum tradeoffs. The dark pattern ranking technique might be carried out by companies once a year to understand the implications of any new dark patterns used.

The advantages of understanding the trade-offs of implementing dark patterns are massive. E-commerce companies can optimize their spent time and resources by implementing the most beneficial dark patterns and avoiding the ones that drive marginal profits and annoy consumers.

This study aims to analyse the components of sustainable business models (SBMs) in the dairy industry, in relation to firm-relevant organisational features (size, ownership structure and production process) and through the lenses of the business model framework and the sustainable value exchange matrix (SVEM). This contribution proposes a taxonomy of emerging SBMs and sustainable value creation in the dairy industry.

This research makes use of a multiple case study approach, with cases selected in collaboration with industry experts. The selected firms are highly committed to sustainability transition. Results are drawn from qualitative data obtained from in-depth interviews and secondary sources. The interpretation phases, initially based on open coding, have been enriched by applying the components of business models (BMs) frameworks and the SVEM, and the analyses have been enhanced through an additional interpretative workshop with experts.

The authors related the BMs characteristics of some typical dairy firms transitioning to sustainability, using SBM components and taxonomies emerging in the literature, based on the formalisation of sustainability practices, the scope of operations, and the degree of integration of the three dimensions of sustainable value. These findings led to the discovery of three types of SBM in this dairy industry, referred to as “Milky Ways”.

This paper contributes to the scant literature on sustainability in dairy firms, highlighting the different paths followed by small and medium-sized enterprises (SMEs), cooperatives and large companies in remoulding their business models towards sustainability and thus achieving sustainable value creation.

This research aims to analyze how companies in the industry act as orchestrators and manage participants in their networks. The service industry has received little attention from scholars in this field, and this research gap was investigated in this study. Qualitative case study research with an exploratory approach is applied in this research so that in-depth insights can be obtained. Mamikos.com, a platform for room rent in Indonesia, was used as the research subject. Mamikos does not only facilitate tenants to find rooms to live in but also manages how landlords can serve tenants better and help tenants understand what the landlords want. In other words, Mamikos seeks to smoothen the value stream from landlords to tenants and vice versa. This research has implications that the value orchestrator must be able to facilitate the parties in the ecosystem to obtain the fundamental values needed and other side values so that they are loyal to the ecosystem managed by the orchestrator.

The global pandemic has increased stakeholders' expectations for companies to protect their health and the wealth of the planet, reason why to achieve long-term social and environmental sustainability, companies need to adopt sustainable business models (SBMs). To support and inspire companies in their journey to become sustainable, the different SBMs that companies can adopt are presented and classified according to their ecological or social focus. It was found that the ecological SBMs follow the circular economy paradigm, and that the social ones can be conceived by considering Base of the Pyramid (BoP) communities.

This study aims to map scientific publications, intellectual structure and research trends in the sustainable business model (SBM) field. Specifically, it attempts to (1) identify the fundamental contributions of research in this area of knowledge; and (2) determine the research lines that constitute the most prominent intellectual structure. We leverage these insights to formulate and propose a future research agenda for SBM.

The authors made recourse to the bibliometric, co-citation and cluster analysis techniques. To evaluate potential patterns among articles, we analysed how articles are jointly cited. We further applied hierarchical cluster analysis to the articles and used co-citation analysis to group the interrelated articles into distinct sets.

The results enable the identification and classification of the prevailing theoretical foci in the domain of SBM: (1) SBM implementation; (2) SBM challenges; (3) institutional SBM; (4) circular SBM; and (5) emerging SBM.

This study identifies, explores, analyses and summarises the main theoretical approaches and themes surrounding SBM research to date, contributing to deepening the literature by identifying the priority areas concerning sustainable business models and encouraging future research of an internationally excellent standard.

The purpose of this study is to develop and validate a taxonomy useful for classifying the training activity preference patterns adopted by executives and for describing how these patterns relate to important workplace measures. Although many organizations hold that well-trained and developed leaders are important for organizational success, little is known about the patterns of self-developmental activities that such leaders choose to initiate and how such training impacts organizational outcomes. Understanding these patterns may be useful in characterizing leaders in terms of training interest and showing a relation between executive training and valued organizational outcomes.

Using a sample of 4,624 senior executives who completed a training activity and attitude survey, cluster analysis was used to derive a five-type training and development (T&D) taxonomy. Types varied by training activity pattern/attitudes and the proportion of well-trained and less-well-trained executives in each agency were described. The researchers collected an independent sample of employee perceptions of engagement and leader effectiveness and number of equal employment opportunity (EEO) complaints within each agency.

Organizations with higher concentrations of well-trained/developed leaders tend to have employees with more favorable workplace attitudes and higher regard for senior leaders and generate smaller proportions of EEO complaints.

Data were collected from 2011 and 2012, government leaders were sampled, and outcome analyses were conducted at the agency level rather than at the individual level.

A link between leader training and organizational outcome is useful for promoting and justifying such training to stakeholders.

Characterizing leaders by training pattern will be useful in examining training usage/interest and in crafting programs tailored to leaders of different patterns.

An executive training pattern taxonomy is unique in the literature and evidence linking such training to outcome is rare.

This study aims to identify the effective operational strategies for airlines in a pandemic that allow them to recover and bounce back smoothly.

This study adopted quantitative methodology based on secondary data published by the airlines related to operational and performance indicators. The total number of airlines surveyed was 145. The sample of study covers all the following regions: Africa, Asia, Europe, the Middle East, North America and South America. The data analysis of this research passed through several phases to compare the situation before and during pandemic period.

The effective operational strategy patterns during the outbreak of the COVID-19 pandemic comprise three hybrid strategies and one scheduling strategy. It appears from these strategy models that four strategic alternatives are available for international airlines to adopt, while two strategic alternatives are available for regional airlines. The strategy alternatives for regional and international airlines are all effective, but those of the international airlines are the more effective ones.

Previous studies rarely adopted the theory of operations strategy configuration (emphasizing taxonomies-based perspective) and the organizational resilience theory (emphasizing capability-based perspective) to identify the effective airlines operations strategy patterns in a pandemic, that allow airlines to recover and bounce back smoothly by analyzing the practices of airlines from different geographic regions worldwide.