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The purpose of this paper is to promote the corrosion resistance of the 5083-111H aluminum alloy by laser cleaning.

Laser with 2 ns pulse width was adopted in this project and the corrosion resistance of cleaned samples was tested by copper-accelerated salt spray (CASS). The surface morphology, elemental composition and distribution were then characterized by SEM. Moreover, surface morphology, elemental composition and distribution were also tested.

Results suggested a higher corrosion resistance was successfully obtained by laser cleaning. Compared with samples cleaned by 2000 grit sandpaper, mechanical cleaning resulted in a 53% larger height difference between the peak and valley. The content of the oxygen is 8.85% on the surface cleaned mechanically and the distribution is dependent on the distribution of aluminum whereas that of the laser cleaning sample is 24.41% and the distribution existed even in the Al-poor area.

In this project, the 2-ns laser cleaning was proved to have the capability to remove the oxide layer on the aluminum alloy surface while retaining an excellent corrosion resistance and smooth surface. Meanwhile, a thorough elemental distribution and smaller grain size lead to a smaller difference in elemental concentration. This retards the diffusion of oxygen into the substrate and hence increases the corrosion resistance of the surface.

The auto ancillary industry in India has witnessed huge capacity expansion and modernization due to entry of foreign automobile manufacturers in the post liberalization era. In spite of potential benefits, the adoption of advanced IT among small to medium‐sized enterprises (SMEs) is low in India. There are several technological, economical and organizational factors that enable or inhibit the adoption of advanced IT. The primary objective of this research is to identify and evaluate the key factors that are enabling or inhibiting adoption of advanced IT in the Indian auto ancillary SMEs.

In order to identify and evaluate the enablers and inhibitors, a detailed survey was carried out among registered Indian auto ancillary SMEs during 2010. Out of 584 registered SMEs, 110 owners/top managers of the SMEs responded to the survey. The data collected through the survey were analyzed using confirmatory factor analysis and multivariate regression to evaluate the influence of enablers and inhibitors of advanced IT adoption by the auto ancillary SMEs.

The survey findings show that the level of advanced IT adoption in auto ancillaries is low with only 17 per cent of SMEs having adopted technologies. This study reveals that “perceived benefits” and “perceived competitive pressure” enable advanced IT adoption among auto ancillary SMEs in India. However, “lack of financial capacity”, “small scale operation and “lack of in‐house IT manpower” inhibit the adoption. It is also found that enablers such as “changes in business environment”, “IT experience of CEO/owner” and “increased information linkage with OEM/customer” do not have any influence on the adoption. Similarly in the case of inhibitors, “lack of IT Infrastructure” and “lack of information security” do not have significant association with IT adoption. Despite the positive external IT environment and recognition of benefits, advanced IT adoption by SMEs in the auto ancillaries is limited by lack of financial capabilities and in‐house IT human resources.

This is one of the early papers that brings out the enablers and inhibitors of advanced IT adoption by auto ancillaries in India. Further, these factors are systematically analyzed to assess the relative importance with reference to the SMEs. The findings contribute to theory of IT adoption among SMEs, but more importantly to the SMEs in the auto ancillary, and policy makers and IT service providers who are likely to facilitate increased adoption.

Since the 2008 financial crisis, the USA has three times implemented quantitative easing (QE) policy. The results of the policy, however, were far below all expectations. Furthermore, it flooded emerging markets (EMs) with low-priced dollars. The purpose of this paper is to investigate the overall and individual impacts of the policy on EMs.

This study uses panel data regression model together with the fixed effects model. Also, a unit root test is conducted to check stationary properties of the data, as well as Durbin-Watson statistic to check serial correlation issues in the models. In estimating empirical models, this paper employs macroeconomic data set of stock market returns, exchange rates, lending interest rates, consumer price index, monetary aggregates and foreign exchange reserves from seven diversified emerging economies. The EMs in this study include China, Indonesia, Singapore, Hong Kong, Taiwan, Russia and Brazil. The time period undertaken in this study is from 2008 to 2012. In order to measure impacts of the different stages of the policy, the authors use dummy variables to represent each stage of the policy.

The results of the study show that the QE policy has significant impacts on foreign exchange reserves, foreign exchange markets and stock markets of the sample economies. Domestic credit markets, however, appear to be least influenced field by the policy. Finally, the results show that only the first stage of the policy exhibits strong significant impacts, however, leverage of the policy decreases over time.

Further studies may use different samples, also variables that measure foreign capital inflows such as changes in financial accounts, foreign direct investment and foreign portfolio investment.

The present study has the following contributions on assessing the impacts of QE policy. First, the overall and individual impacts of the policy are analyzed. Second, in order to establish more valid results, the sample of this study is designed to include several EMs from three continents and diverse regions.

This chapter describes how conversational computer agents have been used in collaborative problem-solving environments. These agent-based systems are designed to (a) assess the students’ knowledge, skills, actions, and various other psychological states on the basis of the students’ actions and the conversational interactions, (b) generate discourse moves that are sensitive to the psychological states and the problem states, and (c) advance a solution to the problem. We describe how this was accomplished in the Programme for International Student Assessment (PISA) for Collaborative Problem Solving (CPS) in 2015. In the PISA CPS 2015 assessment, a single human test taker (15-year-old student) interacts with one, two, or three agents that stage a series of assessment episodes. This chapter proposes that this PISA framework could be extended to accommodate more open-ended natural language interaction for those languages that have developed technologies for automated computational linguistics and discourse. Two examples support this suggestion, with associated relevant empirical support. First, there is AutoTutor, an agent that collaboratively helps the student answer difficult questions and solve problems. Second, there is CPS in the context of a multi-party simulation called Land Science in which the system tracks progress and knowledge states of small groups of 3–4 students. Human mentors or computer agents prompt them to perform actions and exchange open-ended chat in a collaborative learning and problem-solving environment.

Over the last several decades, businesses have faced mounting pressures from diverse stakeholders to alter their corporate operations to become more socially and environmentally responsible. In turn, many firms appear to have responded by implementing more sustainable practices — measuring, documenting, and publishing annual CSR or sustainability reports to showcase how they are addressing important issues in this area, including: resource stewardship, waste management, greenhouse gas emission reductions, fair and safe labor practices, amongst other stakeholder concerns. And yet, research in this domain has not yet systematically examined whether businesses have, on the whole, changed their practices in tandem with the important changes in its institutional context over time. Have corporate CSR initiatives, in fact, been growing over the last 25 years or has the increased attention to CSR actually been much ado about nothing? In this chapter, we review the empirical literature on CSR to uncover that common measures of CSR such as the KLD do not support the concept that CSR practices have increased substantively over the last 25 years. We supplement this historical review by modeling the growth curves of CSR implementation in practice and find that the pace of positive change has indeed been glacial. More alarmingly, we also look at corporate social irresponsibility (CSiR) and find that, contrary to expectations, businesses have become more, not less, irresponsible during this same time period. Implications of these findings for theory are presented as are suggestions for future research in this domain.

Drawing upon the theory of communication visibility, this research intends to investigate the direct effect of enterprise social media (ESM) usage on team members’ knowledge creation capability (KCC) and the mediating effects of psychological safety and team identification. In addition, it aims to untangle how the efficacy of ESM usage varies between pre- and post-COVID-19 periods.

Using two-wave survey data from 240 members nested within 60 teams, this study utilizes a multilevel approach to test the proposed hypotheses.

We discover that ESM usage enhances team members’ KCC. More importantly, the results show that psychological safety and team identification mediate the ESM–KCC linkage. Interestingly, we further find that the impacts of ESM usage on team members’ KCC, psychological safety, and team identification are stronger in the pre-COVID-19 period than those in the post-COVID-19 period.

This research sheds light on the ESM literature by unraveling the mechanisms of psychological safety and team identification underlying the linkage between ESM usage and team members’ KCC. Moreover, it advances our understanding of the differential efficacy of ESM usage in pre- and post-COVID-19 periods.

This paper aims to investigate the issue of information technology (IT) adoption and implementation in Indian manufacturing small‐ and medium‐scale enterprise (SMEs) towards enhancing the capabilities of their supply chain.

Extracts of recently completed case‐based research for ten SME units are utilized for the identification of IT‐enablers. To support the logical deduction of the factors, diagnostic techniques like force‐field analysis, situation‐actor‐process and learning‐action‐performance are used. Further, key managerial insights were obtained by developing an interpretive structural modeling (ISM) model for the set of factors, specific to Indian context.

ISM delivers interrelationships among the factors which were utilized for deriving managerial insights. Further, these factors are classified into four categories, namely, autonomous, driver, dependent, and linkage to understand their relative impact on the implementation of IT in Indian SMEs.

The advancement in IT presents opportunities for SMEs to harness the benefits of information and communication technologies in an affordable, simple way and to reach new customers and suppliers in global competition and at large to improve their supply chain competencies without a need for any major changes in business practices, manufacturing operations or production facilities. The findings of the present research will help Indian SME managers to enable IT implementation with a strategic orientation.

Key issues related to IT implementation in SMEs are discussed and interconnectedness of critical factors for the case of Indian SMEs is understood.

From the intra- and inter-regional dimensions, this paper investigates the linkage between industrial agglomeration and inventory performance, and further demonstrates the moderating role of firm size and enterprise status in the supply chain on this linkage.

Using a large panel dataset of Chinese manufacturers in the Yangtze River Delta for the period from 2008 to 2013, this study employs the method of spatial econometric analysis via a spatial Durbin model (SDM) to examine the effects of industrial agglomeration on inventory performance. Meanwhile, the moderation model is applied to examine the moderating role of two firm-level heterogeneity factors.

At its core, this research demonstrates that industrial agglomeration is associated with the positive change of inventory performance in the adjacent regions, whereas that in the host region as well as in general does not significantly increase. Additionally, both firm size and enterprise status in the supply chain can positively moderate these effects, except for the moderating role of firm size on the positive spillovers.

In view of firm heterogeneity, managers should take special care when matching their abilities of inventory management with the agglomeration effects. Firms with a high level of inventory management are suited to stay in an industrial cluster, while others would be better in the adjacent regions to enhance inventory performance.

This paper is the first to systematically analyze the effects of industrial agglomeration on inventory performance within and across clusters, and confirm that these effects are contingent upon firm size and enterprise status in the supply chain. It adds to the existing literature by highlighting the spatial spillovers from industrial clusters and enriching the antecedents of inventory leanness.

Drawing on the literature on victim precipitation theory, workplace ostracism (WO) and paranoia, this paper examines the mediating role of WO on the paranoia–service performance (SP) relationship. This paper further postulates that team cognitive diversity (TCD) moderates the paranoia–WO relationship.

Data were collected from 228 nurses from a leading hospital located in an eastern province of China. Hypotheses developed from the literature were tested using multivariate hierarchical linear modeling (HLM).

WO had a negative effect on SP, while TCD had a positive effect on WO. Cognitive diversity moderated the paranoia–WO relationship, such that the positive relationship was stronger when group diversity was high.

This paper develops and tests a model exploring the antecedents of WO and its effect on SP.

Creativity and innovation have been buzzwords of managerial discourse over the last few decades as they contribute to the long-term survival and competitiveness of firms. Given the non-linear, causally ambiguous, and intangible nature of all innovation-related phenomena, management scholars have been trying to uncover factors that contribute to creativity and innovation from multiple lenses ranging from organizational behavior at the micro-level to strategic management at the macro-level. Along with important and insightful developments in these research streams that evolved independently from one another, human resource management (HRM) research – especially from a strategic perspective – has only recently started to contribute to a better understanding of both creativity and innovation. The goal of this chapter is to review the contributions of strategic HRM research to an improved understanding of creativity at the individual-level and innovation at the firm-level. In organizing this review, the authors rely on the open innovation funnel as a metaphor to review research on both HRM practices and HRM systems that contribute to creativity and innovation. In the last section, the authors focus on more recent developments in HRM research that focus on ambidexterity – as a way for HRM to simultaneously facilitate exploration and exploitation. This chapter concludes with a discussion of future research directions.