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The purpose of this paper is to reflect on how to apply the abductive research process for developing a theoretical explanation in studies on performance management and management control systems. This is important because theoretically ambitious research tends to require explanatory study outcomes, but prior research frameworks provide little guidance in this regard, potentially facilitating ill-defined research designs and a lack of common vocabulary and criteria for evaluating studies.

The authors introduce a methodological framework that distinguishes three interwoven theoretical abstraction levels: descriptive, analytical and explanatory. They use a recently published qualitative field study to illustrate an application of the framework.

The framework and its illustrated application make the systematic logic of the abductive research process visible and accessible to researchers. The authors explain how the framework supports moving from empirical description to theoretical explanation during the research process and where the three levels might open spaces for the positioning of novel practices and conceptual and theoretical innovations.

The framework provides guidance for an explanatory research design and theory-building purpose and has been developed in response to recent criticism in the field that highlights the wide gap between leading-edge practice and the lagging state of theory. It offers interdisciplinary vocabulary and evaluation criteria that can be applied by any accounting and management researcher regardless of whether they pursue critical, interpretive or positivist research and whether they primarily use qualitative or quantitative research methods.

Health services continue to face economic and capacity challenges. Quality improvement (QI) methods that can improve clinical care processes are therefore needed. However, the successful use of current QI methods within hospital settings remains a challenge. There is considerable scope for improvement of elective clinical pathways, such as hip and knee replacement, and so the use and study of QI methods in such settings is warranted.

A model to manage variability was adapted for use as a QI method and deployed to improve a hip and knee replacement surgical pathway. A prospective observational study, with a mixed-methods sequential explanatory design (quantitative emphasised) that consisted of two distinct phases, was used to assess its effectiveness.

Following the use of the novel QI method and the subsequent changes to care processes, the length of hospital stay was reduced by 18%. However, the interventions to improve care process highlighted by the QI method were not fully implemented. The qualitative data revealed that staff thought the new QI method (the model to manage variability) was simple, effective, offered advantages over other QI methods and had highlighted the correct changes to make. However, they felt that contextual factors around leadership, staffing and organisational issues had prevented changes being implemented and a greater improvement being made.

The quality of QI reporting in surgery has previously been highlighted as poor and lacking in prospective and comprehensively reported mixed-methods evaluations. This study therefore not only describes and presents the results of using a novel QI method but also provides new insights in regard to important contextual factors that may influence the success of QI methods and efforts.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

This paper explores how the International Accounting Standards Board (IASB) has dealt with the emerging issue of accounting for cryptocurrencies by investigating its constituents' expectations and the motivations underlying its regulatory response.

The theoretical lens of regulatory space is used to analyse the four-year debate around cryptocurrency holdings and informs the extensive thematic analysis of public documents, meetings recordings and comment letters on the topic.

Facing national standard setters' initiatives to regulate accounting for cryptocurrency, the IASB defended its position in the regulatory space through an agenda decision based on ewct 2xisting standards, which was finalised by the International Financial Reporting Standards Interpretation Committee (IFRS IC) despite criticism from constituents and Board members.

The paper provides insights into the IASB approach to a regulatory vacuum regarding a new class of items, which derive from a new and rapidly-evolving technology. Disruptive technology impacts the contested arena of accounting regulation, in which the constituents ask for new solutions and the IASB tries to resist such pressures, while defending its position.

The paper sheds light on the growing importance of agenda decisions in the IFRS environment and on the limits of the IASB long regulatory process in the circumstance of emerging accounting issues deriving from rapidly-evolving technology.

This investigation is timely and relevant as it considers the regulatory issues arising from disruptive technological innovations (i.e. cryptocurrency), shedding light on the limits of regulatory processes in times of technological change.

Business model innovation is a key element for firms' competitiveness. Its development can be supported by the establishment of an actor-oriented scheme to overcome hierarchical structures. The actor-oriented scheme is characterized by intra-organizational networks of relationships that can be established and dissolved between individuals. However, we lack an empirical perspective about its establishment; therefore, the purpose of this research is to advance our understanding of intra-organizational networks for supporting business model innovation.

Individuals create and manage knowledge aimed to innovate the business model through cognitive search and experiential learning mechanisms. Knowledge is spread within organizations by using intra-organizational advice networks, whose patterns reflect the presence of an actor-oriented scheme. This work applies social network analysis to network data from a multi-unit organization specializing in personal care services. We use a Logistic Regression-Quadratic Assignment Procedure to analyze intra-organizational network data on managers' advice exchange related to the learning modes of cognitive search and experiential learning.

Our research empirically identifies the main elements of an actor-oriented scheme in a business model innovation process. We find that managers are able to self-organize, because they are not influenced by their organizational roles, and that commons for sharing resources and protocols, processes and infrastructures enable advice exchange, thus showing the presence of an actor-oriented scheme in business model innovation process.

This research is based on a cross-sectional database. A longitudinal study would provide a better understanding of the network evolution characterizing the innovation process.

The results of our study support organizational decision-making for business model innovation.

This study provides empirical evidence of how an actor-oriented scheme emerges in a business model innovation process.

This research aims to investigate the impact of the use of social media on the organizational form and function in selected local governments of Indonesia, Thailand and the Philippines.

This research used quantitative and qualitative methods. The researchers not only conducted comparative– explanatory studies among the three ASEAN cities but also used multiple-informant and secondary data analyses. All variables are operationalized into indicators and transformed into a questionnaire in three languages: English, Indonesian and Thai. Primary data for the research were collected using a cross-sectional survey conducted in Bandung City, Indonesia; Iligan City, the Philippines; and Pukhet City, Thailand.

This research found that social media use has not yet affected the internal organizational processes in the three cities. Also, social media use is not appropriated as a space for citizen–government interaction. It is used for only information dissemination to the public; social media seems to have been used for only collecting information from citizens but not for involving them in the decision-making process.

This research covers only three cities in the ASEAN countries, and the findings cannot be generalized to others. Moreover, this research looks at the supply-side dimension or government organization side only. However, the findings confirm that findings of previous research studies that social media use in the local government is only for information dissemination.

Legal bases for social media use could be an urgent matter to address to advance more fundamental changes in government processes.

There is no prior comparative study on the use of social media by local governments in the ASEAN countries. Social media owing to its sense of personalization or sense of community improves communication between citizens and government better than e-government sites; however, as articulated by Mirchandani et al. (2008), social media may hinder rather than facilitate the delivery of services (Mirchandani et al., 2008). This is due to the absence of a legal basis of its use, as well as agreements on the manner of its use, which prevents full integration of social media into the governance process, particularly in the cases of the cities of Iligan, the Philippines, and Phuket, Thailand.

The purpose of this research is to systematically review the properties of supply chains demonstrating that they are complex systems, and that the management of supply chains is best achieved by steering rather than controlling these systems toward desired outcomes.

The research study was designed as both exploratory and explanatory. Data were collected from secondary sources using a comprehensive literature review process. In parallel with data collection, data were analyzed and synthesized.

The main finding is the introduction of an inductive framework for steering supply chains from a complex systems perspective by explaining why supply chains have properties of complex systems and how to deal with their complexity while steering them toward desired outcomes. Complexity properties are summarized in four inter-dependent categories: Structural, Dynamic, Behavioral and Decision making, which together enable the assessment of supply chains as complex systems. Furthermore, five mechanisms emerged for dealing with the complexity of supply chains: classification, modeling, measurement, relational analysis and handling.

Recognizing that supply chains are complex systems allows for a better grasp of the effect of positive feedback on change and transformation, and also interactions leading to dynamic equilibria, nonlinearity and the role of inter-organizational learning, as well as emerging capabilities, and existing trade-offs and paradoxical tensions in decision-making. It recognizes changing dynamics and the co-evolution of supply chain phenomena in different scales and contexts.

The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.

The purpose of this study is to theorize and test the relationships among lean operations and lean supply chain practices, learning- and innovation-oriented lean cultures and dynamic capabilities (DCs) microfoundations. Further, this study aims to assess the association of DCs microfoundations with process innovation.

The researchers combine primary data collected from 153 manufacturing firms located in five continents using a survey designed for the purpose of this study with archival data downloaded from the Bureau Van Dijk Orbis database and test the hypothesized relationships using structural equation modelling.

Results support the contribution of lean operations and lean supply chain practices to the development of DCs microfoundations, which further lead to greater process innovation. Additionally, while a learning-oriented lean culture positively moderates the relationships between both lean operations and lean supply chain practices and DCs microfoundations, an innovation-oriented lean culture only moderates the relationship between lean operations practices and DCs microfoundations.

This study identifies DCs microfoundations as the key mechanisms for firms implementing lean practices to achieve greater levels of process innovation and the important role played by lean cultures. This study provides direction for managers to put in place DCs through lean implementations, enabling their firms to be ready to respond to challenges and opportunities generated by environmental changes.

While previous research has confirmed the positive effects of lean practices on efficiency, the role of lean practices and cultures in developing capabilities for reacting to environmental dynamism has received little attention. This study offers an empirically supported framework that highlights the potential of lean to adapt processes in response to environmental dynamics, thereby extending the lean paradigm beyond the traditional focus on operational efficiency.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.