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In innovation management, the complexity inherited in the supply network may be necessary for success. This study aims to holistically examine innovation complexities and system attractors within a hierarchically nested supply network and explore how they dynamically interact and influence adaptive innovation processes.

Taking a complexity theory perspective, we employed a methodological bricolage approach using a single case study with multiple embedded units of analysis – namely, a supply network encompassing 36 firms. We drew upon primary data obtained from 42 interviewees and rich secondary data, and we employed a temporal exponential random graph model to examine the micro-foundations of the evolution of the sampled supply network over a decade.

This study presents a comprehensive overview of the innovation complexities—relational, temporal, dynamic, operational and structural – and how they manifest within a supply network. It also identifies three systemic attractors – point, periodic and strange – and elucidates their relationships with the complexities and their impact on innovative supply network dynamics. The resulting conceptual framework and working propositions provide a detailed perspective on the complex interplay between balanced order and chaos and the potentially unbalanced innovation states within a supply network.

This research offers an in-depth perspective on the innovation complexities and dynamic attractors within a supply network from a holistic, multilevel perspective. It advances complexity theory and deepens the understanding of supply networks as complex adaptive systems.

In today’s highly competitive world, the purpose of this research is to emphasize the increasing significance of management education and advocate for the adoption of innovative teaching approaches, specifically focusing on artificial intelligence (AI)-driven personalized learning (PL). This study aims to explore the integration of self-determination theory (SDT) principles into management education, with a primary focus on enhancing student motivation, engagement and academic performance (AP).

This interdisciplinary research adopts a multifaceted approach, combining perspectives from AI, education and psychology. The design and methodology involve a thorough exploration of the theoretical foundations of both AI-driven education and SDT. The research demonstrates how these two elements can synergize to create a holistic educational experience. To substantiate the theoretical claims, empirical data-driven analyses are employed, showcasing the effectiveness of AI-enabled personalized learning (AIPL). The study integrates principles from SDT, such as autonomy, competence and relatedness, to create an environment where students are intrinsically motivated, receiving tailored instruction for optimal outcomes.

The study, rooted in SDT, demonstrates AIPL’s transformative impact on management education. It positively influences students’ autonomy, competence and relatedness, fostering engagement. Autonomy is a key driver, strongly linked to improved AP. The path analysis model validates these relationships, highlighting AI’s pivotal role in reshaping educational experiences and intrinsically motivating students.

This study holds substantial significance for educators, policymakers and researchers. The findings indicate that the AIPL model is effective in increasing student interest and improving AP. Furthermore, this study offers practical guidance for implementing AI in management education to empower students, enhance engagement and align with SDT principles.

Contribute original insights through an interdisciplinary lens. Synthesize AI and SDT principles, providing a roadmap for a more effective educational experience. Empirical data-driven analyses enhance credibility, offering valuable contributions for educators and policymakers in the technology-influenced education landscape.

Green innovation can promote both environmental sustainability and economic growth. However, its development and implementation can be complex due to the need to align innovation activities within and across companies. In this study, the authors examined how this complexity can be managed by analyzing how individual companies combine different innovation activities to develop green innovation, and how companies along the value chain align to implement these innovations.

The dataset comprises both interviews and a survey of senior executives from the Swedish wood construction industry. These data were first analyzed by using fuzzy set qualitative comparative analysis (fsQCA) to identify innovation activity configurations at the level of the individual company. The interviews were then analyzed to identify alignment mechanisms enabling the implementation of green innovation along the value chain.

At the company level, the authors found three innovation activity configurations with varying levels of complexity: (1) systemic innovation by proactive companies, (2) process innovation by reactive companies and (3) inaction by technology-independent companies. On the value chain level, the authors found three alignment mechanisms that facilitate the implementation of green innovation along the value chain. These mechanisms promote cooperation by increasing efficiency, opening up new market opportunities and increasing the level of servitization.

This paper analyzes the complexity of green innovation and provides novel insights into how complexity is managed at the level of both the individual company and the value chain.

This study aims to investigate the interplay between a proactive attitude towards disruptions – supply chain disruption orientation – and supply chain resilience, increasing our understanding of their influence on reducing the impact of supply chain disruptions within the B2B context.

As unexpected disruptions are closely related to a dynamic and changing perception of the environment, this research is framed under the dynamic capabilities lens, consistent with existing resilience literature. The authors used partial least squares-path modeling (PLS-PM) to empirically test the proposed research model using survey data from 216 firms.

Results show that a proactive approach to disruptions alone is insufficient in mitigating their negative impact. Instead, a firm’s disruption orientation plays a crucial role in boosting its resilience, which acts as a mediator, reducing the impact of disruptions.

This paper sheds light on the mechanisms by which firms can mitigate the effects of supply chain disruptions and offers insights into how certain capabilities are needed so that firms’ attitudes can effectively impact firm performance. This research thus suggests that dynamic capabilities, traditionally perceived as being enabled by other elements, act themselves as enablers. Consequently, they have the potential to translate strategic orientation or attitudes into tangible effects on performance, enriching our understanding of how firms combine their internal attitudes and capabilities to achieve sustained competitive advantage.

This study illustrates the economic and financial dynamics of the sector, analysing the evolution of the main ratios of profitability and financial structure of 1,559 Italian real estate companies divided into the three macro-regions: North, Centre and South, in the period 2011–2020. In this way, it is also possible to verify the responsiveness to the 2020 pandemic crisis.

The analysis uses descriptive statistics tools and the ANOVA method of analysis of variance, supplemented by the Tukey–Kramer test, to identify significant differences between the three Italian macro-regions.

The study shows the increase in profitability after the 2008 crisis, despite its reverberation in the years 2012–2013. The financial structure of companies improved almost everywhere. The pandemic had modest effects on performance.

In the future, other indices should be considered to gain a more comprehensive view. This is a quantitative study based on financial statements data that neglects other important economic and social factors.

Public policies could use this study for better interventions to support the sector. In addition, internal management can compare their company's performance with the industry average to identify possible improvements.

The research analyses an economic field that employs a large number of people, especially when considering the construction and real estate services covered by this analysis.

The study contributes to the literature by providing a quantitative analysis of industry dynamics, with comparative information that can be deduced from financial statements over the years.

The field of website quality evaluation attracts the interest of a range of disciplines, each bringing its own particular perspective to bear. This study aims to identify the main characteristics – methods, techniques and tools – of the instruments of evaluation described in this literature, with a specific concern for the factors analysed, and based on these, a multipurpose model is proposed for the development of new comprehensive instruments.

Following a systematic bibliographic review, 305 publications on website quality are examined, the field's leading authors, their disciplines of origin and the sectors to which the websites being assessed belong are identified, and the methods they employ characterised.

Evaluations of website quality tend to be conducted with one of three primary focuses: strategic, functional or experiential. The technique of expert analysis predominates over user studies and most of the instruments examined classify the characteristics to be evaluated – for example, usability and content – into factors that operate at different levels, albeit that there is little agreement on the names used in referring to them.

Based on the factors detected in the 50 most cited works, a model is developed that classifies these factors into 13 dimensions and more than 120 general parameters. The resulting model provides a comprehensive evaluation framework and constitutes an initial step towards a shared conceptualization of the discipline of website quality.

The present study is aimed at examining the antecedents of online shopping user behavior and customer satisfaction. More specifically, (1) the effect of social influence, variety seeking behavior, advertising and convenience on user behavior, and (2) the effect of user behavior on customer satisfaction are examined.

A conceptual model is developed and tested after verifying the psychometric properties of the survey instrument. Data were collected from 556 respondents from three major cities (Hyderabad, Chennai and Bangalore) in the southern part of India using structured instrument. Hierarchical regression is performed. Measurement model was checked using structural equation modeling (Lisrel package).

The results reveal that (1) social influence, (2) variety seeking, (3) advertising, (4) convenience, (5) trust and (6) product factors were positively related to online user behavior. Results also show that user behavior is significantly and positively related to customer satisfaction. The hierarchical regression results also showed moderating effects of (1) trust in the relationship between social influence, variety seeking and user behavior, and (2) product factors in the relationship between advertising, convenience and user behavior. Finally, results suggest that user behavior is partially mediating the relationship between trust and customer satisfaction, i.e. trust has both direct and indirect effect on customer satisfaction.

As with any survey-based research, the present study suffers from the problems associated with self-report measures viz., common method bias and social desirability bias. However, the authors attempted to minimize these limitations by following appropriate statistical techniques.

This study contributes to both practicing managers and the literature on advertising. The study suggests that trust and product play a major role in strengthening the relationship between antecedents and user behavior.

This study provides new insights about the importance of gaining trust in influencing consumer behavior. The conceptual model the authors developed is novel in the sense not many studies are available in India to empirically examine the moderating relationships of trust and product in consumer behavior.