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For start-ups or growing firms, to effectively navigate the unpredictable nature of digital development and achieve superior innovative performance, it is crucial to have a workforce comprised of creative and innovative employees. Drawing upon the principles of social information processing theory, this study aims to investigate whether specific combinations of organizational internal and external environments, as well as work characteristics in the digital age, can foster a high level of employee innovative behavior.

By collecting a multilevel and multisource data set comprising 693 employees and 88 CEOs from 88 start-ups or growing firms, this study used fuzzy-set qualitative comparative analysis to examine the distinctive configurations associated with achieving a high level of employee innovative behavior.

The study found that six solutions enabled employees to innovate more effectively, but six solutions led to the absence of employee innovative behavior.

The findings of this study offer important theoretical and practical implications to motivate employee innovative behavior in Chinese enterprises.

First, this study contributes to the literature on employee innovative behavior by addressing the need to explore the impact of the digital context on promoting innovation among employees. Second, this study adds to the existing literature on employee innovation and entrepreneurship by examining multiple organizational contexts and their influence on innovative behavior. Third, this study makes a significant contribution to the field of employee innovative behavior by examining the macroenvironment surrounding digital transformation within enterprises and integrating both internal and external organizational factors.

This study aims to identify the causes of the academia-industry divide in hospitality marketing research in the form of the “Research Devaluation Map” and offers ideas for discussion points and suggestions for change.

The conceptualization of the Research Devaluation Map was developed at an invitational thought-leadership conference. The authors were asked to produce a forward looking, critical reflection of hospitality marketing scholarship. The authors generated a preliminary idea and developed a methodology for its implementation. They then proposed a framework that explicated the divide between hospitality marketing research and industry practice and a list of discussion points regarding possible solutions.

The issues currently challenging the hospitality research field are found to include the choice of research topics (the “what”), the methods used in research (the “how”) and the systemic factors that shape the academic culture (the “systemic”). These three factors lead to a mutual devaluation of the academic–industry relationship in hospitality marketing, causing a schism between research and industry practice.

The Research Devaluation Map serves as a springboard for future research studies, providing a framework for naming and operationalizing the antecedents and results of the divide between hospitality marketing research and practice.

This paper takes a holistic look at the gaps in current hospitality marketing research and puts forth a framework to explain the roots of these issues. While certain of these issues are known to both researchers and practitioners, the originality of this paper lies in the creation of the Research Devaluation Map that identifies the causes and results of the disconnect between research and practice.

Software defect prediction (SDP) is a critical aspect of software quality assurance, aiming to identify and manage potential defects in software systems. In this paper, we have proposed a novel hybrid approach that combines Gray Wolf Optimization with Feature Selection (GWOFS) and multilayer perceptron (MLP) for SDP. The GWOFS-MLP hybrid model is designed to optimize feature selection, ultimately enhancing the accuracy and efficiency of SDP. Gray Wolf Optimization, inspired by the social hierarchy and hunting behavior of gray wolves, is employed to select a subset of relevant features from an extensive pool of potential predictors. This study investigates the key challenges that traditional SDP approaches encounter and proposes promising solutions to overcome time complexity and the curse of the dimensionality reduction problem.

The integration of GWOFS and MLP results in a robust hybrid model that can adapt to diverse software datasets. This feature selection process harnesses the cooperative hunting behavior of wolves, allowing for the exploration of critical feature combinations. The selected features are then fed into an MLP, a powerful artificial neural network (ANN) known for its capability to learn intricate patterns within software metrics. MLP serves as the predictive engine, utilizing the curated feature set to model and classify software defects accurately.

The performance evaluation of the GWOFS-MLP hybrid model on a real-world software defect dataset demonstrates its effectiveness. The model achieves a remarkable training accuracy of 97.69% and a testing accuracy of 97.99%. Additionally, the receiver operating characteristic area under the curve (ROC-AUC) score of 0.89 highlights the model’s ability to discriminate between defective and defect-free software components.

Experimental implementations using machine learning-based techniques with feature reduction are conducted to validate the proposed solutions. The goal is to enhance SDP’s accuracy, relevance and efficiency, ultimately improving software quality assurance processes. The confusion matrix further illustrates the model’s performance, with only a small number of false positives and false negatives.

This study addresses the prevailing complexities and limitations in estimating and managing construction overhead costs (COCs) in the existing literature, with the purpose of enhancing the accuracy of cost performance indicators in construction project management.

An innovative approach is proposed, employing the activity-based costing (ABC) accounting method combined with building information modelling (BIM) to assign real overhead costs to project activities. This study, distinguished by its incorporation of a real case study, focuses on an administrative building with a four-story concrete structure. It establishes an automated method for evaluating project cost performance through the detailed analysis of earned value management (EVM) cost indicators derived from ABC results and BIM data.

The results show that the ABC integration improves the accuracy of cost performance indicators by over 9%, revealing the project's true cost index for the first time and demonstrating the substantial value of the approach in construction engineering and management.

The current study highlights a notable gap in the existing literature, addressing the challenges in onsite overhead cost estimation and offering a solution that incorporates the state-of-the-art techniques.

The proposed method has significant implications for project managers and practitioners, enabling better-informed decisions based on precise cost data, ultimately leading to enhanced project outcomes.

This research uniquely combines ABC and BIM, presenting a pioneering solution for the accurate estimation and management of COCs in construction projects, adding significant value to the current body of knowledge in this field.

Design-thinking (DT) in education has attracted significant interest from practitioners and academics, as it proffers new-age thinking to transform learning processes. This paper synthesises extant literature and identifies the current intellectual frontiers.

First, a systematic-literature-review was undertaken employing a robust process of selecting papers (from 1986 to 2022) by reading titles, abstracts and keywords based on a required criterion, backward–forward chaining and strict quality evaluations. Next, a bibliometric analysis was undertaken using VOSviewer. Finally, text analysis using RStudio was done to trace the implications of past work and future directions.

At first, we identify and explain 12 clusters through bibliometric coupling that include “interdisciplinary-area”, “futuristic-learning”, “design-process” and “design-education”, amongst others. We explain each of these clusters later in the text. Science, Technology, Engineering, Arts and Mathematics (STEAM), management education, design and change, teacher training, entrepreneurship education and technology, digital learning, gifted education and course development) Secondly, through co-word-analysis, we identify and explain four additional clusters that include “business education and pedagogy”, “content and learning environment”, “participants and outcome” and finally, “thinking-processes”. Based on this finding, we believe that the future holds a very positive presence sentiment for design thinking and education (DT&E) in changing the 21st century learning.

For investigating many contemporary challenges related to DT&E, like virtual reality experiential learning, sustainability education, organisational learning and management training, etc. have been outlined.

Academics may come up with new or improved courses for the implementation of DT in educational settings and policymakers may inculcate design labs in the curricula to fortify academic excellence. Managers who would employ DT in their training, development and policy design, amongst others, could end up gaining a competitive advantage in the marketplace.

This study conducted a comprehensive review of the field, which to our limited knowledge, no prior studies have been done so far. Besides, the study also outlines interesting research questions for future research.

In recent years, issues like untrusted or questionable sources of information are indisputably rampant in the digital era. The quality of information is now found to be challenging with its kind of issues, crisis and also clarity in which it requires to have a strategic scenario and practice to enhance quality assurance in order to creating safe cyber-spaces. The initiative to organise information at the organisational stage has widely emerged on the cyberspace. This paper aims to examine the insights of the element of trust in quality communication and information management to drive key performance indicator to support organisational sustainability. This approach is likely to play a significant role in enhancing critical inquiry in to issue of trust in information to ensure untainted integrity and quality assurance of the source of the information.

The preparation of this paper used a systematic literature review according to four phases, namely, identification, assessment or examination, extraction and interpretation. This approach was selected to advance critical inquiry into the most current topic on the trust for quality of information as way of strategic communication management to achieve safe cyber-organisational sustainability. The process was made through the various sources of peer-reviewed articles including journals, book chapters, books and conference proceedings. The literature review was carried out through the search for keywords such as trust in information, strategic communication and safe cyber-organisational sustainability.

The results revealed that the trust in quality of information with its wide range of initiatives could be enhanced as an initial attempt to embrace comprehensive approach in establishing strategic communication to ensure organisational sustainability and quality assurance of safe cyber space. The result further indicated three points, which follows development of virtual interaction with information management for safe cyberspace, enhancing continued predictability assessment in digital information process and practice and developing trust in information and quality of communication for organisational sustainability.

This paper is expected to give an insightful value in contributing to quality measurement of the strategic communication to promote trust in quality of information. Hence, the design to expand strategic management to support digital social connections in the cyber space. As a result, the profound contribution would also lead to enhancement of organisational sustainability in the digital era, amid technological trends.

The need to develop an approach to strengthen the trust in information in the digital cyberspace should focus on providing insights into the quality of information, authenticity and integrity to develop quality assurance for social connection. The awareness raising process in consolidating the trust in information has to start with exploring early social interaction in the digital age. This approach provides quality assurance to linking digital connection to develop trust in the quality of information. This would enable feedback to ensure accessibility and accuracy of quality of information dealing with critical elements relating to organisational sustainability.

The entire awareness in expanding the trust as information quality indicator has to be started with exploring the early social interaction in the digital age, to achieve quality basis on linking the digital connection as an attempt to build the information quality. This would give a feedback in ensuring the accessibility and accuracy of information quality together with dealing with an ultimate element to lead to the organisational longevity.

This study aims to simultaneously examine customer complaints through the proposed novel Design for Six Sigma (DFSS) model which incorporates of creating the new insurance services to win customers' hearts and mind for the insurance industry.

A novel DFSS research methodology which includes the theory of inventive problem solving (TRIZ), Pugh concept selection, creative product analysis matrix and importance–satisfaction model (I–S Model) was proposed. In addition, a real insurance company case was studied to illustrate the effectiveness of the proposed DFSS model.

The results of a novel DFSS model not only can establish new services, but also can dramatically reduce the cost of resolving customer complaints.

The findings of this study are useful for insurance companies and other related service providers in devising tailored strategies to offer quality and suitable services to their customers.

This study addresses the paucity of research and marketing gaps through the proposed novel DFSS model for the first time in the insurance industry. These study findings would enable researchers and practitioners to formulate strategies for solving customer complaints effectively and develop new services from time to time.

The purpose of this paper is to present a framework of ideation pathways that organically extend the current stock of knowledge to generate new and useful knowledge. Although detailed, granular guidance is available in the strategy literature on all aspects of empirically testing theory, the other key aspect of theory development – theory generation – remains relatively neglected. The framework developed in this paper addresses this gap by proposing pathways for how new theory can be generated.

Grounded in two foundational principles in epistemology, the Genetic Argument and the open-endedness of knowledge, I offer a framework of distinct pathways that systematically lead to the creation of new knowledge.

Existing knowledge can be deepened (through introspection), broadened (through leverage) and rejuvenated (through innovation). These ideation pathways can unlock the vast, hidden potential of current knowledge in strategy.

The novelty and doability of the framework can potentially inspire research on a broad, community-wide basis, engaging PhD students and management faculty, improving knowledge, democratizing scholarship and deepening the societal footprint of strategy research.

Knowledge is open-ended. The more we know, the more we appreciate how much we don’t know. But the lack of clear guidance on rigorous pathways along which new knowledge that advances both theory and practice can be created from prior knowledge has stymied strategy research. The paper’s framework systematically pulls together for the first time the disparate elements of transforming past learning into new knowledge in a coherent epistemological whole.

Of critical concern to the world is the need to reduce consumption and waste of natural resources. This study provides a multi-level exploration of the ways situational and transformational links between levels and challenges are related to the adoption and utilization of material flow cost accounting in Vietnam, to encourage green productivity.

Based on triangulation of public documents at different institutional levels and a set of semi-structured interviews, situational and transformational links and challenges for material flow cost accounting in Vietnam are examined using purposive and snowball sampling of key actors.

Using a multi-level framework the research identifies six situational and transformational barriers to implementation of material flow cost accounting and suggests opportunities to overcome these. The weakest links identified involve macro-to meso-situational and micro-to macro-transformational links. The paper highlights the dominance of meso-level institutions and lack of focus on micro transformation to cut waste and enable improvements in green productivity.

The paper identifies ways for companies in Vietnam to reduce unsustainability and enable transformation towards sustainable management and waste reduction.

The paper is the first to develop and use a multi-level/multi-time period framework to examine the take-up of material flow cost accounting to encourage transformation towards green productivity. Consideration of the Vietnamese case builds understanding of the challenges for achieving United Nations Sustainable Development Goal number 12, to help enable sustainable production and consumption patterns.

The purpose of this research is to develop a framework of an ontology-based Asset Information Model (AIM) for a Digital Twin (DT) platform and enhance predictive maintenance practices in building facilities that could enable proactive and data-driven decision-making during the Operation and Maintenance (O&M) process.

A scoping literature review was accomplished to establish the theoretical foundation for the current investigation. A study on developing an ontology-based AIM for predictive maintenance in building facilities was conducted. Semi-structured interviews were conducted with industry professionals to gather qualitative data for ontology-based AIM framework validation and insights.

The research findings indicate that while the development of ontology faced challenges in defining missing entities and relations in the context of predictive maintenance, insights gained from the interviews enabled the establishment of a comprehensive framework for ontology-based AIM adoption in the Facility Management (FM) sector.

The proposed ontology-based AIM has the potential to enable proactive and data-driven decision-making during the process, optimizing predictive maintenance practices and ultimately enhancing energy efficiency and sustainability in the building industry.

The research contributes to a practical guide for ontology development processes and presents a framework of an Ontology-based AIM for a Digital Twin platform.