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Competitiveness is an important personality trait that has been studied in various disciplines and has been shown to predict critical work outcomes at the individual level. Despite this, the role of competitiveness in groups and teams has received scant attention amongst organizational researchers. Aiming to promote future research on the role of competitiveness as both an adaptive and maladaptive trait – particularly in the context of work – the authors review competitiveness and its effects on individual and team stress and Well-Being, giving special attention to the processes of cohesion and conflict and situational moderators. The authors illustrate a dynamic multilevel model of individual and team difference factors, competitive processes, and individual and team outcomes to highlight competitiveness as a consequential occupational stressor. Furthermore, the authors discuss the feedback loops that inform the different factors, highlight important avenues for future research, and offer practical solutions for managers to reduce unhealthy competition.

The purpose of this study is to revisit the conventional wisdom about a key contribution [i.e. strengths, weaknesses, opportunities, threats (SWOT) analysis] in the field of strategic management. The societal context and the role of academics, consultants and executives is taken into account in the emergence of SWOT analysis during the 1960–1980 period as a pivotal development within the broader context of the satisfactory, opportunities, faults, threats (SOFT) approach. The authors report on both the content and the approach, so that other scholars seeking to invigorate indigenous theories and/or underreported strategy practices will thrive.

Applying a historiographic approach, the authors introduce an evidence-based methodology for interpreting historical sources. This methodology incorporates source criticism, triangulation and hermeneutical interpretation, drawing upon insights from robust evidence through three iterative stages.

The underreporting of the SOFT approach/SWOT analysis can be attributed to several factors, including strategy tools being integrated into planning frameworks rather than being published as standalone materials; restricted circulation of crucial long-range planning service/theory and practice of planning reports due to copyright limitations; restricted access to the Stanford Research Institute Planning Library in California; and the enduring popularity of SOFT and SWOT variations, driven in part by their memorable acronyms.

In the spirit of a renaissance in strategic planning research, the authors unveil novel theoretical and social connections in the emergence of SWOT analysis by combining evidence from both theory and practice and delving into previously unexplored areas.

Caution is advised for scholars who examine the discrete time frame of 1960–1980 through mere bibliometric techniques. This study underscores the risks associated with gathering incomplete and/or inaccurate data, emphasizing the importance of triangulating evidence beyond scholarly databases. The paradigm shift of strategic management research due to the advent of large language models poses new challenges and the risk of conserving and perpetuating academic urban legends, myths and lies if training data is not adequately curated.

Recognising the as-built state of construction elements is crucial for construction progress monitoring. Construction scholars have used computer vision-based algorithms to automate this process. Robust object recognition from indoor site images has been inhibited by technical challenges related to indoor objects, lighting conditions and camera positioning. Compared with traditional machine learning algorithms, one-stage detector deep learning (DL) algorithms can prioritise the inference speed, enable real-time accurate object detection and classification. This study aims to present a DL-based approach to facilitate the as-built state recognition of indoor construction works.

The one-stage DL-based approach was built upon YOLO version 4 (YOLOv4) algorithm using transfer learning with few hyperparameters customised and trained in the Google Colab virtual machine. The process of framing, insulation and drywall installation of indoor partitions was selected as the as-built scenario. For training, images were captured from two indoor sites with publicly available online images.

The DL model reported a best-trained weight with a mean average precision of 92% and an average loss of 0.83. Compared to previous studies, the automation level of this study is high due to the use of fixed time-lapse cameras for data collection and zero manual intervention from the pre-processing algorithms to enhance visual quality of indoor images.

This study extends the application of DL models for recognising as-built state of indoor construction works upon providing training images. Presenting a workflow on training DL models in a virtual machine platform by reducing the computational complexities associated with DL models is also materialised.

In the evolving digital work landscape, where cyberloafing has become a notable challenge, this study aims to investigate the mechanisms through which organizations can effectively reduce such behaviors. Specifically, the research explores the role of employee adaptability in mitigating cyberloafing, taking into account the influences of temporal leadership, teamwork attitudes, and competitive work environments.

Utilizing the broaden-and-build theory and the job demands-resources (JD-R) model, we analyzed data from 245 employees through structural equation modeling (SEM) to investigate how various factors influence cyberloafing.

The results indicate that employee adaptability significantly mitigates cyberloafing and serves as a mediating factor between temporal leadership, teamwork attitudes, and the impact of competitive work environments on cyberloafing. Temporal leadership and teamwork attitudes positively correlate with increased adaptability, thereby reducing cyberloafing. Conversely, competitive work environments, while slightly enhancing adaptability, substantially increase cyberloafing.

The study contributes new insights into the dynamics of cyberloafing, emphasizing the critical roles of adaptability, teamwork attitudes, and temporal leadership in reducing such behaviors. It underscores the need for organizations to foster a supportive culture that minimizes competitive pressures and promotes teamwork and leadership strategies conducive to high productivity and minimal cyberloafing. This research offers practical implications for designing workplace strategies aimed at boosting productivity and curbing undesirable online behaviors during work hours.

In recent years, the acronym VUCA has gained traction in strategic communication (SC) as an umbrella term that summarizes the recurrent challenges (volatility, uncertainty, complexity and ambiguity) of digital communication environments. However, an integrated reflection on how the VUCA dimensions facilitate a deeper understanding of specific digitalization challenges and how to navigate through these challenges is lacking. This article aims to explore and substantiate the descriptive (how) and prescriptive (how to) potential of VUCA for SC under digitalization conditions.

We first provide a systematic discussion of the four VUCA dimensions based on the general strategy literature. While their descriptive value is undisputed, prescriptive advice on how to respond to these challenges is contradictory. We substantiate this observation in a second empirical step based on problem-centered interviews with strategic communicators at the agency and corporate levels.

Our findings reveal that VUCA facilitates a systematic mapping of digitalization challenges consistently identified by professionals. The proposed strategic responses, however, remain contradictory at the theoretical and empirical levels. Hence, we propose the VUCA radar as a comprehensive descriptive and prescriptive framework.

The radar provides (a) a systematic overview of recurrent digitalization challenges to SC at the industry and practice levels and (b) prescriptive advice on how to navigate through these challenges by balancing contradictory strategic responses at the levels of vision, understanding, clarity and agility.

A “state-driven” approach suggests that colonists use census categories to rule. However, a “society-driven” approach suggests that this state-driven perspective confers too much power upon states. A third approach views census-taking and official categorization as a product of state–society interaction that depends upon: (a) the population's lay categories, (b) information intellectuals' ability to take up and transform these lay categories, and (c) the balance of power between social and state actors. We evaluate the above positions by analyzing official records, key texts, travelogues, and statistical memoirs from three key periods in India: Indus Valley civilization through classical Gupta rule (ca. 3300 BCE–700 CE), the “medieval” period (ca. 700–1700 CE), and East India Company (EIC) rule (1757–1857 CE), using historical narrative. We show that information gathering early in the first period was society driven; however, over time, a strong interactive pattern emerged. Scribes (information intellectuals) increased their social status and power (thus, shifting the balance of power) by drawing on caste categories (lay categories) and incorporating them into official information gathering. This intensification of interactive information gathering allowed the Mughals, the EIC, and finally British direct rule officials to collect large quantities of information. Our evidence thus suggests that the intensification of state–society interactions over time laid the groundwork for the success of the direct rule British censuses. It also suggests that any transformative effect of these censuses lay in this interactive pattern, not in the strength of the British colonial state.