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The purpose of this study is to determine how sonic logo’s acoustic features (intensity, pitch and pace) based on melodic tunes with no voice orient the response of consumers, attract attention, elicit levels of pleasantness and calmness and transmit brand personality traits.

A within-subject experimental factorial design is applied to measure emotional arousal (indexed as electrodermal activity) and enhancement on perceptual processing (indexed as heart rate), as well as self-reported factors, namely, calmness/excitement, pleasantness and brand personality scales.

Results show a significant increase on electrodermal activity associated with fast-paced sonic logos and a decrease in heart rate in slow-paced long sonic logos. Also, fade-up, pitch-ascending fast sonic logos are defined as more exciting and descending-pitch sonic logos as more pleasant.

The use of sonic logos with no voice does limit its implications. Besides, the use of three variables simultaneously with 18 versions of sonic logos in a laboratory setting may have driven participants to fatigue; hence, findings should be cautiously applied.

First, sonic logos are best processed in a fade-up form. Second, fast pace is recommended to orient response, whereas slow pace is recommended to transmit calmness. Practitioners may opt for fast-paced sonic logos if the design is new or played in a noisy environment and opt for slow-paced sonic logos in already highly recognized sound designs.

To the best of authors’ knowledge, this study is the first to combine psychophysiological measures and self-reported scales in a laboratory experiment on how sonic logo’s acoustic features orient response, transmit emotions and personality traits.

This paper aims to explore how the time and temporal aspects are managed in a financial accounting outsourcing (FAO) transition process in an international interorganizational context. As a research outcome, the authors identify management interventions of both the service provider (SP) and the outsourcing company (OC) at both the corporate and operational levels.

The framework by Huy (2001a, 2001b) was used to analyze the qualitative data, which draw on observations, participation in 32 official meetings during the outsourcing process, informal discussions with key actors from the SP and the OC, and archival data of a single case company.

The authors illustrate how the time and temporal aspects of planned accelerated change are managed through management interventions during the FAO transition process. All four ideal intervention types (commanding, engineering, teaching and socializing) were used sequentially but also jointly to complement one another. The pacing was mostly rapid, owing to strong commanding interventions initiating almost every stage. When analyzing the FAO transition process, the authors identified four stages: contact, contract, convergence and control. Moreover, the authors focused on the role of the operational-level managers and accounting specialists of both organizations. The findings indicate that management interventions vary with the management level.

This study contributes to the interorganizational control literature by considering the time and temporal aspects in planned organizational change and the role of operational-level managers in managing large-scale changes.

At the dawn of a new decade, as ever more corporations are pursuing sustainable working conditions and advocating employee well-being, employees are increasingly tending to feel fatigued and drained by their work, which compromises their performance. Drawing on the job demands–resources model and social acceleration debate, the authors test a moderated mediation model. Specifically, the authors hypothesise that unreasonable tasks raise perceptions of emotional exhaustion when the pace of work is increased and investigate the moderating role of psychological detachment.

This study used a sample of 245 employees from Europe, all knowledge workers, to test the hypotheses.

Apart from unreasonable tasks being directly related with emotional exhaustion, this relationship was mediated by the perceived work pace. In addition, the authors establish psychological detachment as a relevant moderator for the mediating effect.

Managers and HR practitioners are equipped with a better understanding of the effects of an increasing speed of work, the conditions leading to it and the individual and organizational resources that may help to create healthy and meaningful job positions, which facilitate employee efficiency.

Our study expands the literature on contemporary stressors and adds to what is known about the ‘dark side’ of job demands that affect the organizational bottom-line, as well as the resource-based mechanism that can buffer the negative effects.

COVID-19 has forced Big 4 firms to challenge existing management control arrangements and adapt their ways of working. Yet, we know little about how management control might be enacted in the future of the sustainable workplace. The objective of the study is to examine the patterns of management control change in the Big 4 accounting firms during the COVID-19 pandemic.

Adopting an exploratory qualitative research design, the authors draw on 42 interviews with directors and associates in the Big 4 professional services firms.

The findings reveal two pathways of management control change including alignment and displacement. The authors found that relatively minor adaptions to action and result controls were relied upon to respond to substantial cultural and personnel control changes.

The contributions are threefold: the authors take a temporal perspective to (1) unpack the changes to management control arrangements; (2) theorise the findings by developing a three-dimensional taxonomy of change pathways encompassing pace, scope and longevity of management control change and (3) contextualise management control arrangements in a hybrid work setting.

1. COVID-19 has forced Big 4 firms to challenge existing management control arrangements.

2. Literature has focused on traditional, onsite work settings and largely ignored change pathways.

3. The authors take a temporal perspective to unpack changes to management control arrangements.

4. Big 4 firms adapted to hybrid work with substantial changes to personnel and cultural controls.

5. The authors theorise the findings by developing a three-dimensional taxonomy of change pathways.

COVID-19 has forced Big 4 firms to challenge existing management control arrangements.

Literature has focused on traditional, onsite work settings and largely ignored change pathways.

The authors take a temporal perspective to unpack changes to management control arrangements.

Big 4 firms adapted to hybrid work with substantial changes to personnel and cultural controls.

The authors theorise the findings by developing a three-dimensional taxonomy of change pathways.

Disruptive technologies in the global logistics industry are often regarded as a threat to the existing business models of incumbents’ companies. Existing research, however, focuses mainly on whether technologies have disruptive potential, thereby neglecting when such disruptive transitions occur. To understand the timing of potential disruptive technological change, this paper aims to investigate the elements of the underlying ecosystem shaping these transitions.

Building on the established ecosystem framework from Adner and Kapoor (2016a), this paper constructs four categories of technology substitution to assess how quickly disruptive change may occur in the global logistics industry and defines key technology substitution determinants in logistics to emphasize the role of ecosystems for further consideration into disruptive innovation theory.

Based on the key determinants, this paper proposes first definitions of distinctive ecosystems elements linked to the three types of innovations, namely, sustaining innovations, low-end disruptions and new-market disruptions, thereby integrating ecosystems into Christensen’s (1997) disruptive innovation theory.

By developing a framework that conceptualizes the pace of technology substitution, this paper contributes to a more nuanced understanding of how logistics managers and academics can better predict disruptive transitions and develop strategies to allocate resources.

The present paper aims to highlight how manufacturing expansions under conditions of increasing returns, which involve the growth of intermediate goods specializations, support advanced service employment. In addition, the increasing use of manufacturing products in services highlights additional, new service sector employment opportunities.

This paper investigates (1) the manufacturing and service interactions and (2) the investment behaviour in manufacturing using Auto-Regressive Distributed lags (ARDL) and Vector Autoregressive (VAR) models. The models allow for different specifications to study whether investment behaviour in manufacturing supports dynamic manufacturing and service interactions.

The results underpin how Kaldorian manufacturing as an engine of growth is still relevant in Indian growth and is key to achieving higher advanced employment, export-orientation and services and manufacturing nexus outcomes. What matters, though, is that manufacturing investments are to be guided mainly by intermediate goods specializations. The slowdown of these specializations, explaining the slowdown of manufacturing investment, is therefore, a concern.

A reinterpretation of manufacturing as an engine of growth in which primacy is given to investment behaviour in technical progress functions that can support the growth of specializations in manufacturing and such specialized service employment.

Recent advancements in Artificial Intelligence (AI) and, at its core, Machine Learning (ML) offer opportunities for organizations to develop new or enhance existing capabilities. Despite the endless possibilities, organizations face operational challenges in harvesting the value of ML-based capabilities (MLbC), and current research has yet to explicate these challenges and theorize their remedies. To bridge the gap, this study explored the current practices to propose a systematic way of orchestrating MLbC development, which is an extension of ongoing digitalization of organizations.

Data were collected from Finland's Artificial Intelligence Accelerator (FAIA) and complemented by follow-up interviews with experts outside FAIA in Europe, China and the United States over four years. Data were analyzed through open coding, thematic analysis and cross-comparison to develop a comprehensive understanding of the MLbC development process.

The analysis identified the main components of MLbC development, its three phases (development, release and operation) and two major MLbC development challenges: Temporal Complexity and Context Sensitivity. The study then introduced Fostering Temporal Congruence and Cultivating Organizational Meta-learning as strategic practices addressing these challenges.

This study offers a better theoretical explanation for the MLbC development process beyond MLOps (Machine Learning Operations) and its hindrances. It also proposes a practical way to align ML-based applications with business needs while accounting for their structural limitations. Beyond the MLbC context, this study offers a strategic framework that can be adapted for different cases of digital transformation that include automation and augmentation of work.

The purpose of this paper is to share the lessons learned in implementing specific design patterns within the “Dr Internet” massive open online course (MOOC).

MOOCs are boasting considerable participant numbers, but also suffer from declining participant activity and low completion rates. Learning analytics results from earlier xMOOCs indicate that this might be alleviated by certain instructional design patterns – critical aspects include shorter course duration, narrative structures with suspense peaks, and a course schedule that is diversified and stimulating. To evaluate their impact on retention, the authors have tried to implement these patterns in the design of the “Dr Internet” MOOC.

Statistical results from the first run of the case study MOOC do not indicate any strong influences of these design patterns on the retention rate.

With inconclusive statistical results from this case study, more research with higher participant numbers is needed to gain insight on the effectiveness of these design patterns in MOOCs. When interpreting retention outcomes, other influencing factors (course content, pacing, timing, etc.) need to be taken into account.

This publication reports about a case study MOOC and gives practical hints for further research.

The purpose of this study is to explore learner-centered emerging technologies, methods of learning with artificial intelligence (AI), student engagement and concerns related to the assessment process at public and private universities in Bangladesh.

The study employed a qualitative research approach to investigate innovations in learning, student engagement and assessment concerns. Respondents were categorized into three clusters: Cluster-A comprised students from various academic levels, Cluster-B included faculty members with online teaching experience and Cluster-C consisted of information and communication technology (ICT) experts from university information technology (IT) departments. Qualitative data were collected via in-depth interviews.

The research findings indicate the widespread acceptance and utilization of learner-centered technologies, with online and hybrid learning offering flexibility, accessibility, self-paced learning and better student engagement opportunities. While AI platforms like ChatGPT and Gemini are valued for clarifying theoretical concepts, concerns exist regarding their ethical use, particularly in completing assignments. The assessment process faces challenges related to online exams, with concerns over cheating prompting calls for AI-supported solutions. However, there is a gap between commitment and action in regulating unethical AI usage, highlighting the need for clearer guidance and investment in technological solutions for an effective assessment process.

Limitations of this study include the inability to quantify the satisfaction level with the emergence of learner-centered technologies, which could be better explained through a quantitative study.

This study’s originality and value stem from its thorough investigation of innovations in learner-centered education considering the emergence of AI and student engagement, uniquely focusing on the perspective of a developing country.

The study aims to understand digital transformation as a socially constructed process with multiple stakeholders, influenced by internal and external forces. This perspective stresses the importance of context, human interaction and narratives in the digital transformation within public sector.

The author uses a case study at a Swedish university undergoing digital transformation. Through first and secondary data, the author thematically analyzes the interaction between change agents, organizational realities and the digital transformation process.

The study finds that conflicts in pace and scope in the digital transformation drive self-defense mechanisms and the formation of a feedback loop of pending action. Contrary to previous studies, technological and external forces do not make digital transformation inevitable.

Limitations stem from the empirical selection of a Swedish university, affecting the international and intersectoral transferability of the study. The impact of digital transformation differs from previous IT changes, which has implications for the design of the digital transformation process.

Stakeholders should, instead of considering structural and cultural barriers as facts, pay attention to the narratives within the organization as potential excuses to avoid action.

This research contributes to original insights into digital transformation. It uncovers how change agents, despite longing for change, can inadvertently foster inaction in digital transformation. This finding enriches the literature by highlighting the complex dynamics between the desire for change and the social constructs that contribute to stagnation, offering an understanding of barriers to digital transformation.