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By taking a social learning perspective, this study examines the trickle-down effect of empowering leadership across hierarchical levels in an organization. Specifically, this study aims to demonstrate that the empowering leadership of higher-level leaders promotes the task performance of employees through the mediation of the empowering leadership of lower-level leaders. It also seeks to confirm the role of performance pressure as a boundary condition in social learning process.

Under a moderated mediation framework, this study tests our hypotheses through a hierarchical regression analysis. The data used in the analysis is from the survey responses of 209 subordinate-supervisor dyads.

This study finds that the empowering leadership of higher-level leaders promotes the empowering leadership of lower-level leaders, which indirectly improves the task performance of employees. It also finds that performance pressure perceived by lower-level leaders moderates the relationship between the empowering leadership of higher- and lower-level leaders, thus moderating the proposed indirect effect.

This study complements the findings of previous studies by identifying the trickle-down effect of empowering leadership across different hierarchical levels in an organization and by highlighting its boundary condition. In addition, this study provides evidence for the presence of trickle-down effect of leadership in an Eastern culture.

This study suggests the necessity of leadership education and training programs within organizations by revealing the importance of social learning process for promoting empowering leadership. In addition, it also suggests that performance pressure in an organization not only dampens empowering leadership but also has a negative effect on the task performance of employees.

This study demonstrates the influence mechanism of empowering leadership through a systematic verification of its trickle-down effect, which has been lacking in previous studies. It also highlights the moderating role of performance pressure, as a contextual factor, in the social learning and influence process of empowering leadership.

The growing prevalence of social entrepreneurship has been coupled with an increasing number of so-called “impact investors”. However, much remains to be learned about this nascent class of investors. To address the dearth of scholarly attention to impact investing, this study seeks to answer four questions that are central to understanding the phenomenon. What are the defining characteristics of impact investing? Do impact investors differ from traditional classes of investors and, if so, how? What are the motivations that drive impact investment? And, what criteria do impact investors use when evaluating potential investments?

A partially inductive study based on semi-structured interviews with 31 investors and ethnographic observation was conducted to explore how impact investors differ from other classes of investors in their motivations and unique criteria used to evaluate ventures seeking investment.

This study reveals that impact investors represent a unique class of investors that differs from socially responsible investing, from other types of for-profit investors, such as venture capitalists and angel investors, and from traditional philanthropists. The varied motivations of impact investors and the criteria they use to evaluate investments are identified.

Despite the growing practitioner and media attention to impact investing, several foundational issues remain unaddressed. This study takes the first steps toward shedding light on this new realm of early-stage venture investing and clarifying its role in larger efforts of social responsibility.

This paper aims to study a parameter tuning method for the active disturbance rejection control (ADRC) to improve the anti-interference ability and position tracking of the performance of the servo system, and to ensure the stability and accuracy of practical applications.

This study proposes a parameter self-tuning method for ADRC based on an improved glowworm swarm optimization algorithm. The algorithm is improved by using sine and cosine local optimization operators and an adaptive mutation strategy. The improved algorithm is then used for parameter tuning of the ADRC to improve the anti-interference ability of the control system and ensure the accuracy of the controller parameters.

The authors designed an optimization model based on MATLAB, selected examples of simulation and experimental research and compared it with the standard glowworm swarm optimization algorithm, particle swarm algorithm and artificial bee colony algorithm. The results show that the response time of using the improved glowworm swarm optimization algorithm to optimize the auto-disturbance rejection control is short; there is no overshoot; the tracking process is relatively stable; the anti-interference ability is strong; and the optimization effect is better.

The innovation of this study is to improve the glowworm swarm optimization algorithm, propose a sine and cosine, local optimization operator, expand the firefly search space and introduce a new adaptive mutation strategy to adaptively adjust the mutation probability based on the fitness value, improve the global search ability of the algorithm and use the improved algorithm to adjust the parameters of the active disturbance rejection controller.

This paper aims to introduce the concept of top management team (TMT) regulatory focus to explain the differences in executive motivation. Upper echelons research has demonstrated that top managers’ willingness to deviate from their current strategies is a key determinant of organizational success. However, it is not clear why some TMTs are motivated to embrace strategic change while others are motivated to favor the strategic status quo.

Recent work in the psychology of motivation is used to develop a conceptual model explaining how the regulatory focus of TMTs can impact their outlooks toward strategic change.

It is theorized that there is a positive (negative) relationship between promotion (prevention)-focused TMTs and strategic change. It is also theorized that executives’ performance aspirations, firm maturity and the stability of the environment will influence the relationship between regulatory focus and strategic change.

Although the theoretical explanations provided by past research on top manager motivation are psychological in their general focus, with few exceptions research has not sought to understand the specific deep-level, socio-cognitive characteristics that shape executives’ perceptions of strategic change. By developing an understanding of the psychological determinants of strategic change, as well as the interplay between these determinants and firm- and environment-level factors, this paper represents a step in the direction of explaining why some TMTs are motivated to embrace strategic change while others seem “locked-in” to the status quo.

Roofing is one of the most dangerous jobs in the construction industry. Due to factors such as lack of planning, training and use of precaution, roofing contractors and workers continuously violate the fall protection standards enforced by the US Occupational Safety and Health Administration. A preferable way to alleviate this situation is automating the process of non-compliance checking of safety standards through measurements conducted in site daily accumulated videos and photos. As a key component, the purpose of this paper is to devise a method to detect roofs in site images that is indispensable for such automation process.

This method represents roof objects through image segmentation and visual feature extraction. The visual features include colour, texture, compactness, contrast and the presence of roof corner. A classification algorithm is selected to use the derived representation for statistical learning and detection.

The experiments led to detection accuracy of 97.50 per cent, with over 15 per cent improvement in comparison to conventional classifiers, signifying the effectiveness of the proposed method.

This study did not test on images of roofs in the following conditions: roofs initially built without apparent appearance (e.g. structural roof framing completed and undergoing the sheathing process) and flat, barrel and dome roofs. From a standpoint of construction safety, while the present work is vital, coupling with semantic representation and analysis is still needed to allow for risk analysis of fall violations on roof sites.

This study is the first to address roof detection in site images. Its findings provide a basis to enable semantic representation of roof site objects of interests (e.g. co-existence and correlation among roof site, roofer, guardrail and personal fall arrest system) that is needed to automate the non-compliance checking of safety standards on roof sites.

The device, amplifies and sub-regionally transmits the current generated by the body temperature thermoelectric generator through a smart body temperature sensor.

The present study designs a wearable smart device regarding the relationship between temperature and emotion.

Experimental results show that the device can accurately detect changes in human body temperature under hilarious, fearful, soothing and angry emotions, so as to achieve changes in clothing colors, namely blue, red, green and brown.

Different areas of clothing produce controllable and intelligent color, so that adult emotions can be understood through changes in clothing colors, which is conducive to judging their moods and promoting social interaction.

Many scholars and practitioners in the fields of business and management have recently published theoretical and empirical studies on the subject of business culture and its impact on its growth and effectiveness; yet, there has been a dearth of research on the topic of how organizational culture affects productivity. Moreover, there are hardly any theoretical or empirical research that examines these two concepts within the context of a micro-enterprise. This chapter uses a sample of 279 Ancash Region microenterprises to investigate the effect of local entrepreneurial culture on businesses’ overall performance. Among the four types of entrepreneurial cultures studied, only the Hierarchical culture was shown to have no effect on the degree of performance of the microenterprises. There is evidence of a significant causal relationship between the variables studied, the coefficient of determination was; business performance (r² = 0.796), with an SRMR of 0.037, the confirmatory model is relevant within its range of accuracy, while market culture has the greatest impact on business performance.

The authors analyze the impact of COVID-19 on listed European electricity companies and differentiate between renewable and traditional electricity, to show the heterogenous characteristics of electricity subsectors and the differences between renewable and traditional electricity.

Using the event study method, the authors calculate the cumulative average abnormal returns (ARs) before and after the World Health Organization pandemic announcement and the declaration of national lockdowns in Europe.

The results show that while the European electricity sector was overall negatively impacted by the COVID-19 announcement, this impact was larger for renewable companies due to their riskier investment profile. Moreover, after the national lockdowns came into effect, the recovery in the financial markets return was smaller for the latter.

There may be variables to be included in the model to analyze possible differences between companies and countries, as well as alternative econometric models. Limited to the data, the authors did not investigate the different impact of the economic policy uncertainty from various countries inside or outside the EU.

The results have important implications for both investors and policymakers since the heterogenous characteristics of electricity subsectors. This heterogeneity prompts different investor reactions, which are necessary to know and to understand.

As far as the authors know, this is the first study that analyses the effect of COVID-19 in heterogeneity profile of both types of electricity, renewable and traditional.

The purpose of this study is to synthesize the previous empirical studies on transactive memory systems (TMS) through a meta-analytical approach and test the proposed model for the relationships between TMS and different types of team outcomes.

TMS refers to shared memory systems developed among a group of people for encoding, storage and retrieval of their different knowledge domains. They have been widely used in group or organization settings to describe the cumulative knowledge in a group of multi-disciplinary experts. Previous literature suggests TMS as a critical concept for explaining group performance, but few studies were conducted to integrate the literature findings to identify the relationships between TMS and team outcomes.

The findings suggest that TMS is more strongly linked to affective outcomes than behavioral or performance outcomes. In addition, the authors find that the specific operationalization of TMS does not affect the relationship between TMS and team outcomes. There was not enough support for significant effects of group size and research setting on the relationships between TMS and team outcomes, which indicates that both laboratory and field studies have similar potential to generate valuable results for the research of TMS.

This study contributes to the body of knowledge on team effectiveness by investigating the links between TMS and team effectiveness through a broad definition of outcomes that include tangible constructs, such as performance, as well as behavioral and affective outcomes. By exploring the relationships through this broad conceptualization of team effectiveness, the authors can better understand the particular effects of TMS on different key aspects used to determine success in teams.