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The aim of this study is to test for a moderating role of employee participation in volunteering in links between employees' relationships with peers and supervisors, work meaningfulness (WM) and affective commitment (AC).

The study is based on a survey conducted on a sample of 711 employees, both those involved and those non-involved in corporate volunteering (CV).

The results suggest that employee participation in CV strengthens the effects that employees' perceptions of positive relationships with peers and perceived supervisor support (PSS) have on employees' AC. Contrary to expectations, although participation in CV strengthens employees' sense of WM, it does not affect its links with other phenomena analyzed in this study.

CV is a fast-growing practice in corporate social responsibility. The reasons companies implement CV include the benefits they gain from it, such as positive effects on employee attitudes and behaviors. The paper contributes to the understanding of CV effects on employee attitudes and behaviors and builds a better business case for this CSR practice.

Banks play a vital role in the economy. Investigating their competitive environment is crucial to ensuring economic stability and development. The FinTech disruption has risks and opportunities for incumbent banks, and it can be valuable to investigate its effects on banking performance. Therefore, the aim of this study is to assess whether investment in FinTech is associated with better performance of Indian banks during 2012–2018.

To do this, a sample of Indian banks was investigated between 2012 and 2018 using k-means and hierarchical cluster analysis, ANOVA, and pairwise comparison tests.

Results of the analysis strongly suggest that investment in FinTech is associated with better banking performance. Higher FinTech investments, represented by mobile transaction volume, are associated with higher efficiency scores and accounting-based performance. In particular, banks that invest in FinTech and have relatively low non-performing loans have a 7.7% higher Return on Employment (ROE) than banks with exceptionally low FinTech use and no significant investment in smart branches.

Therefore, it can be recommended that Indian banks adopt a forward-looking strategic approach when making investment decisions regarding new technologies. Failing to adapt to the FinTech disruption may result in poor value creation prospects in the long run.

To the best of the authors' knowledge, this is the first study that analyses. We are not aware of any similar study on whether investment in FinTech is associated with better performance of the Indian banks during 2012–2018.

Global proliferation had a noteworthy impact on the Indian retail banking industry and mushrooming banks have entailed to emphasize on customer satisfaction (CS) quotient to remain competitive. This study aims to illuminate determinants of CS and customer trust (CT) and their denouement in Indian retail banking.

The top six Indian private sector banks were selected hinged on market capitalization. A total of 460 responses from retail bank customers were gathered using a structured questionnaire. Direct and indirect relationships were analyzed with mediation and moderation by using structural equation modeling.

The study identifies determinants of CS and CT. The results manifest that perceived service innovation (PSI) and bank reputation (BR) considerably aggrandize CS and CT. Furthermore, CS strikingly magnifies customer loyalty (CL). The study also posits that CT partially mediates between the nexus of PSI and BR on the one side and CS on the other. Moreover, perceived risk moderates the association between CS and loyalty.

The study demonstrates indispensable drivers of CS, CT and CL which may encourage bank professionals to hold on to their customers and enhance profitability.

Here is a dearth of literature on PSI and BR in the Indian banking industry. Thus, the study supplements literature by assimilating these constructs through a compendious conceptual model. The study is distinct as it evaluates mediating effects of CT in unfurling complexities of relationships among the underlying constructs.

A significant increase in the number of private sector banks has intensified the level of competition in the Indian banking industry (IBI). This increase in the number of banks has a considerable impact on the existing players, which calls for prioritizing customer satisfaction (CS) and enhancing bank reputation (BR). Our study seeks to investigate the enablers of CS and BR in the IBI.

The study adopted a cross-sectional design for gathering responses from retail bank customers across the selected banks through a structured questionnaire. Structural equation modeling (SEM) was utilized to evaluate direct and indirect linkages among the identified constructs by examining mediating and moderating effects.

The study puts forward crucial antecedents of CS and BR. The findings exhibit that perceived trust (PT) and relationship commitment (RC) magnify CS and BR, respectively, while CS amplifies repurchase intention (RI). The study advances that BR and CS partially mediate between the underlying constructs. In addition, fairness and risk exhibit moderating effects between CS and customer repurchase intention (CRI) and BR and CRI.

The study illustrates the crucial enablers of BR, CS and CRI that may assist banking professionals in enriching customer experience and holding on to their customers.

There is a shortage of research on RC, service innovation (SI) and BR in the IBI. Accordingly, our study builds on the prior studies by considering these constructs using a comprehensive conceptual framework by extending the application of signaling theory (ST) in the banking domain and scrutinizing the dual moderating effects of fairness and risk.

Aluminum nitride (AlN) ceramics are suitable substrate and package materials for high-power integrated circuits.

Dense AlN ceramics with Y₂O₃ and LaF₃ as sintering additives are prepared. The effects of these additives on the density, phase composition, microstructure and thermal conductivity of AlN ceramics are investigated.

Results show that 2 Wt.% Y₂O₃-doped additive is insufficient for the samples to achieve the full densification sintered at 1,700°C. When LaF₃ is added with Y₂O₃, the samples are perfectly densified at the same sintering condition. The relative density and thermal conductivity of the samples are 97.8-99.07 per cent and 169.104-200.010 W·m-1·K-1, respectively. The density of the samples and their microstructure, especially the content and distribution of secondary phases, is necessary to control the thermal conductivity of AlN ceramics.

Y₂O₃ and LaF₃ additives can effectively promote densification and enhance the thermal conductivity of AlN ceramics in a low sintering temperature, and the AlN ceramics added with Y₂O₃-LaF₃ might have potential applications in package materials for high-power integrated circuits.

Consumer purchasing behavior (CPB) plays a crucial role within the hospitality sector, specifically in restaurants situated in China, as it directly impacts the performance and profitability of businesses. In this context, there is a need to assess the factors influencing CPB. Therefore, this research seeks to inspect the influence of consumer attitudes (CA) on interpersonal influences (II) and CPB. Additionally, seeks to explore the mediation of II and the moderation of corporate social responsibility (CSR).

This study utilized cross-sectional data obtained through online surveys. To analyze the data, structural equation modeling was employed.

The research unveils a substantial and positive association between CA, II and CPB. It also found that II partially mediates CA and CPB association. Moreover, CSR was identified as a moderator in the connection between CA and CPB.

The implications of this study are of great significance for companies operating in the hospitality industry. They indicate that cultivating favorable CA and promoting II, while considering CSR initiatives, can effectively augment overall purchasing behavior. As a result, it can contribute to the achievement of business success.

This study offers a unique perspective on the factors driving purchasing behavior, shedding light on how businesses can enhance their performance and profitability in this specific setting.

In the implementation of large-size additive manufacturing (AM), the large printing area can be established by using the tiled and fixed multiple printing heads or the single dynamic printing head moving in the x–y plane, which requires a layer decomposition after the mesh slicing to generate segmented infill areas. The data processing flow of these schemes is redundant and inefficient to some extent, especially for the processing of complex stereolithograph (STL) models. It is of great importance in improving the overall efficiency of large-size AM technics software by simplifying the redundant steps. This paper aims to address these issues.

In this paper, a method of directly generating segmented layered infill areas is proposed for AM. Initially, a vertices–mesh hybrid representation of STL models is constructed based on a divide-and-conquer strategy. Then, a trimming–mapping procedure is performed on sliced contours acquired from partial surfaces. Finally, to link trimmed open contours and inside-signal square corners as segmented infill areas, a region-based open contour closing algorithm is carried out in virtue of the developed data structures.

In virtue of the proposed approach, the segmented layered infill areas can be directly generated from STL models. Experimental results indicate that the approach brings us the good property of efficiency, especially for complex STL models.

The proposed approach can generate segmented layered infill areas efficiently in some cases.

The region-based layered infill area generation approach discussed here will be a supplement to current data process technologies in large-size AM, which is very suitable for parallel processing and enables us to improve the efficiency of large-size AM technics software.

The digital revolution and the use of big data (BD) in particular has important applications in the construction industry. In construction, massive amounts of heterogeneous data need to be analyzed to improve onsite efficiency. This article presents a systematic review and identifies future research directions, presenting valuable conclusions derived from rigorous bibliometric tools. The results of this study may provide guidelines for construction engineering and global policymaking to change the current low-efficiency of construction sites.

This study identifies research trends from 1,253 peer-reviewed papers, using general statistics, keyword co-occurrence analysis, critical review, and qualitative-bibliometric techniques in two rounds of search.

The number of studies in this area rapidly increased from 2012 to 2020. A significant number of publications originated in the UK, China, the US, and Australia, and the smallest number from one of these countries is more than twice the largest number in the remaining countries. Keyword co-occurrence is divided into three clusters: BD application scenarios, emerging technology in BD, and BD management. Currently developing approaches in BD analytics include machine learning, data mining, and heuristic-optimization algorithms such as graph convolutional, recurrent neural networks and natural language processes (NLP). Studies have focused on safety management, energy reduction, and cost prediction. Blockchain integrated with BD is a promising means of managing construction contracts.

The study of BD is in a stage of rapid development, and this bibliometric analysis is only a part of the necessary practical analysis.

National policies, temporal and spatial distribution, BD flow are interpreted, and the results of this may provide guidelines for policymakers. Overall, this work may develop the body of knowledge, producing a reference point and identifying future development.

To our knowledge, this is the first bibliometric review of BD in the construction industry. This study can also benefit construction practitioners by providing them a focused perspective of BD for emerging practices in the construction industry.

This study aims to explore the relationship between the innovation capacity and performance of manufacturing firms in the Ecuadorian pharmaceutical and chemical sectors using strategic foresight analysis.

From an extensive literature review, the fundamental variables related to manufacturing firms’ innovation for better performance were identified. Six hypotheses and actions were proposed related to financing, economic resources, capacities and research and development. Several scenarios were tested through foresight methodology to determine the more appropriate to be implemented by manufacturing firms over the next five years.

Scenario 01, where all the hypotheses resulted positive, has a 15.3% probability of occurrence. The results offer a relevant understanding of the behavior of the variables proposed as strategic actions for the sector.

To the best of the authors’ knowledge, foresight methodology is applied for the first time to analyze the manufacturing sector in Ecuador. The authors propose a plan of action from the strategic scenario identified in this study, supporting the development of the industrial sectors under study.

An alliance portfolio can help latecomer firms to acquire the necessary knowledge and resources to catch up with market leaders. However, how latecomer firms construct an alliance portfolio in terms of the nature of windows of opportunity has not been fully analyzed. This paper aims to explore how latecomer firms can build appropriate coalitions according to the nature of the window of opportunity to achieve technological catch-up in different catch-up phases.

Based on a longitudinal case study from 1984 to 2018 of Sunny Group, now a leading manufacturer of integrated optical components and products, this paper explores the process of technological catch-up of latecomer firms building different types of alliance portfolio in different windows of opportunity.

This paper finds that there is a sequence when latecomers build an alliance portfolio in the process of catch-up. When the uncertainty of opportunity increases, the governance mechanism of the alliance portfolio will change from contractual to equity-based. Also, latecomer firms build market-dominated and technology-dominated alliance portfolios to overcome their market and technology disadvantages, respectively.

These conclusions not only enrich the theory of latecomer catch-up from the perspective of windows of opportunity but also expand research on alliance portfolio processes from a temporal perspective.