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The purpose of this paper is to contribute to empirical evidence by recognizing the importance of stock markets in the financial system and consequently its causality to economic growth and vice versa.

The study used the autoregressive distribute lag model (ARDL) with bound testing procedures, the sample covered quarterly time-series data from 2001q1 to 2019q2 in Tanzania.

The results suggest that stock market development have both negative and positive causality for both short-run dynamics and long-run relationship with economic growth. Economic growth is found to only cause and relate negatively to liquidity both in the short-run and in the long-run. The results show predominantly a unidirectional causality flow from stock market development to economic growth and finds partial causality flow from economic growth to stock market development, as represented by stock market turnover which proxied liquidity.

The use of quarterly data to reflect more realistically the dynamics of the variables because yearly data may sometimes cover-up specific dynamics that may be useful for prediction and policy planning. The study uses indices to capture general aspects within the stock market against economic growth as an intuitive way to aggregate the stock market development effects.

We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis demonstrates that, under these conditions, the perpetual put option consistently commands a higher price during periods of high volatility compared to those of low volatility. Moreover, we establish that the optimal exercise boundary is lower in high-volatility regimes than in low-volatility regimes. Additionally, we develop an analytical framework to describe American puts with an Erlang-distributed random-time horizon, which allows us to propose a numerical technique for approximating the value of American puts with finite expiry. We also show that a combined approach involving randomization and Richardson extrapolation can be a robust numerical algorithm for estimating American put prices with finite expiry.

Industry 4.0 (I 4.0) consists of numerous digital technologies applied in organizations strategically to add value to the customer. Different organizations have varying degrees of technological capability and strategic flexibility. This paper aims to explore the relationship between technological capability and strategic flexibility on successful implementation of I 4.0.

A qualitative study using a grounded theory approach is conducted on 34 senior managers from Europe and North America who have implemented I 4.0 participated in this study through a theoretical sampling frame.

This study finds that technological capability and strategic flexibility have an impact on the successful implementation of I 4.0. The study also finds that different dimensions of technological capability also impact I 4.0. The interactive effect of strategic flexibility and technological capability is also noted. The study also develops a framework for successful implementation of I 4.0.

This study can be used by managers while implementing I 4.0 to devise a strategic roadmap for acquiring technological capability with I 4.0 technologies. Besides, it will help the managers to consider the bidirectional relationship between technological capability and strategic flexibility while formulating I 4.0 strategy for successful implementation of I 4.0 in their organizations.

Previous studies have examined the importance of I 4.0 technologies. However, this study extends the previous works by suggesting how technological capability and strategic flexibility can help in the successful implementation of I 4.0.

In the age of digital media, customers have access to vast digital information sources, within and outside a company's direct control. Yet managers lack a metric to capture customers' cross-media exposure and its ramifications for individual customer journeys. To solve this issue, this article introduces media entropy as a new metric for assessing cross-media exposure on the individual customer level and illustrates its effect on consumers' purchase decisions.

Building on information and signalling theory, this study proposes the entropy of company-controlled and peer-driven media sources as a measure of cross-media exposure. A probit model analyses individual-level customer journey data across more than 25,000 digital and traditional media touchpoints.

Cross-media exposure, measured as the entropy of information sources in a customer journey, drives purchase decisions. The positive effect is particularly pronounced for (1) digital (online) versus traditional (offline) media environments, (2) customers who currently do not own the brand and (3) brands that customers perceive as weak.

The proposed metric of cross-media exposure can help managers understand customers' information structures in pre-purchase phases. Assessing the consequences of customers' cross-media exposure is especially relevant for service companies that seek to support customers' information search efforts. Marketing agencies, consultancies and platform providers also need actionable customer journey metrics, particularly in early stages of the journey.

Service managers and marketers can integrate the media entropy metric into their marketing dashboards and use it to steer their investments in different media types. Researchers can include the metric in empirical models to explore customers' omni-channel journeys.

Isu diskriminasi antara kaum telah tular di media sosial berikutan isu pemberian vaksin secara jumpa terus yang mula dibukakan di Pusat Vaksinasi Stadium Tertutup pada hari Jumaat, 24 September 2021. Jumlah orang ramai yang ingin mengambil vaksin telah melebihi jangkaan sehingga menyebabkan keadaan menjadi tidak terkawal dan berlakunya pelanggaran Prosedur Pengendalian Standard (SOP). Kajian ini dijalankan untuk membincangkan isu diskriminasi kaum yang berlaku semasa gelombang kedua pandemik COVID-19. Penelitian menggunakan metode kualitatif secara deskriptif. Data yang diperolehi daripada komen-komen dalam halaman Brunei Dot Com, dan Facebook ini seterusnya dianalisis menggunakan model tiga dimensi Fairclough (1992). Hasil kajian mendapati kesemua komen telah menunjukkan sikap diskriminasi dalam kalangan masyarakat Brunei secara sedar ataupun tidak. Isu diskriminasi ini bukan sahaja dapat dilihat dari sudut representasi linguistik, tetapi juga penghasilan dan pewahanaan wacana berkaitan pada halaman Brunei Dot Com, dan Facebook. Kajian ini juga menunjukkan bahawa wacana bukan saja mampu dibentuk masyarakat tetapi juga membentuknya.

The issue of racial discrimination concerning the commencement of walk-in vaccination at the Indoor Stadium Vaccination Centre on Friday, 24 September 2021 was widely addressed in the social media. Chaos ensued as an influx of people attended the centre and violated the Standard Operating Procedure (SOP). This paper examines the issue of racial discrimination during the second wave of COVID-19 pandemic in Brunei. As a qualitative-descriptive study, data obtained from Brunei Dot Com, and Facebook page, were analysed using Fairclough's (1992) three-dimensional approach. Findings have shown presence of discriminatory attitudes among the local community displayed as deliberately or unintentionally. This is manifested in its linguistic representations, discourse production and consumption in the selected Brunei Dot Com and Facebook pages. This study indicates that a discourse is not only capable of shaping but is also shaped by the community.

In recent years, owing to the rapidly increasing labor costs, the demand for robots in daily services and industrial operations has been increased significantly. For further applications and human–robot interaction in an unstructured open environment, fast and accurate tracking and strong disturbance rejection ability are required. However, utilizing a conventional controller can make it difficult for the robot to meet these demands, and when a robot is required to perform at a high-speed and large range of motion, conventional controllers may not perform effectively or even lead to the instability.

The main idea is to develop the control law by combining the SMC feedback with the ADRC control architecture to improve the robustness and control quality of a conventional SMC controller. The problem is formulated and solved in the framework of ADRC. For better estimation and control performance, a generalized proportional integral observer (GPIO) technique is employed to estimate and compensate for unmodeled dynamics and other unknown time-varying disturbances. And benefiting from the usage of GPIO, a new SMC law can be designed by synthesizing the estimation and its history.

The employed methodology introduced a significant improvement in handling the uncertainties of the system parameters without compromising the nominal system control quality and intuitiveness of the conventional ADRC design. First, the proposed method combines the advantages of the ADRC and SMC method, which achieved the best tracking performance among these controllers. Second, the proposed controller is sufficiently robust to various disturbances and results in smaller tracking errors. Third, the proposed control method is insensitive to control parameters which indicates a good application potential.

High-performance robot tracking control is the basis for further robot applications in open environments and human–robot interfaces, which require high tracking accuracy and strong disturbance rejection. However, both the varied dynamics of the system and rapidly changing nonlinear coupling characteristic significantly increase the control difficulty. The proposed method gives a new replacement of PID controller in robot systems, which does not require an accurate dynamic system model, is insensitive to control parameters and can perform promisingly for response rapidity and steady-state accuracy, as well as in the presence of strong unknown disturbances.

This paper is supposed to provide a critical review of current research progress on thermal management in grinding of superalloys, and future directions and challenges. By understanding the current progress and identifying the developing directions, thermal management can be achieved in the grinding of superalloys to significantly improve the grinding quality and efficiency.

The relevant literature is collected from Web of Science, Scopus, CNKI, Google scholar, etc. A total of 185 literature is analyzed, and the findings in the literature are systematically summarized. In this case, the current development and future trends of thermal management in grinding of superalloys can be concluded.

The recent developments in grinding superalloys, demands, challenges and solutions are analyzed. The theoretical basis of thermal management in grinding, the grinding heat partition analysis, is also summarized. The novel methods and technologies for thermal management are developed and reviewed, i.e. new grinding technologies and parameter optimization, super abrasive grinding wheel technologies, improved lubrication, highly efficient coolant delivery and enhanced heat transfer by passive thermal devices. Finally, the future trends and challenges are identified.

Superalloys have excellent physical and mechanical properties, e.g. high thermal stability, and good high-temperature strength. The superalloys have been broadly applied in the aerospace, energy and automobile industries. Grinding is one of the most important precision machining technologies for superalloy parts. Owing to the mechanical and physical properties of superalloys, during grinding processes, forces are large and a massive heat is generated. Consequently, the improvement of grinding quality and efficiency is limited. It is important to conduct thermal management in the grinding of superalloys to decrease grinding forces and heat generation. The grinding heat is also dissipated in time by enhanced heat transfer methods. Therefore, it is necessary and valuable to holistically review the current situation of thermal management in grinding of superalloys and also provide the development trends and challenges.

The purpose of this paper is to better understand the role of virtual teams in organizational transformation. This conceptual paper explores the significant influence of the digital era on organizational structures, specifically focusing on the transformative shift toward virtual teams (VTs) with a strong message for small and medium-sized enterprises (SMEs).

The article is based on the review of existing concepts identified in the previously published studies and their critical reflection. The literature search was conducted in the Web of Science database in May 2024 by using the keywords VTs, Digitalization and SMEs.

In the rapidly changing business environment, organizational transformation is no longer a choice but a prerequisite for the survival and growth of businesses. It is argued in the study that organizations, especially SMEs, need to embrace VT despite the challenge of a comprehensive theoretical framework for understanding VT and the need for the development of a novel theory, which has been a reoccurring phenomenon and subject of debate in the literature. Furthermore, the paper underlines the necessity of providing essential preparation and training for VTs, focusing on both technological skills and collaborative work methods. In the context of SMEs, the paper argues that collaboration with external partners and the adoption of virtuality can enhance competitiveness. In the end, the emergence of virtual learning communities is proposed as a solution, providing a platform for SME owners/managers to share experiences and acquire new skills.

Overall, this study provides several recommendations for future research on VTs.

In a first of its kind, this paper tries to explore the long-run relationship between investors' sentiment and selected industries' returns over the period January 2010 to December 2021.

The paper uses 23 market and macroeconomic proxies to measure investor sentiment. Principal component analysis has been used to create sentiment sub-indices that represent investor sentiment. The autoregressive distributed lag (ARDL) model and other sophisticated econometric techniques such as the unit root test, the cumulative sum (CUSUM) stability test, regression, etc. have been used to achieve the objectives of the study.

The authors find that there is a significant relationship between sentiment sub-indices and industries' returns over the period of study. Market and economic variables, market ratios, advance-decline ratio, high-low index, price-to-book value ratio and liquidity in the economy are some of the significant sub-indices explaining industries' returns.

The study has relevant implications for retail investors, policy-makers and other decision-makers in the Indian stock market. Results are helpful for the investor in improving their decision-making and identifying those sentiment sub-indices and the variables therein that are relevant in explaining the return of a particular industry.

The study contributes to the existing literature by exploring the relationship between sentiment and industries' returns in the Indian stock market and by identifying relevant sentiment sub-indices. Also, the study supports the investors' irrationality, which arises due to a plethora of behavioral biases as enshrined in classical finance.

The study aims to examine the appropriateness of the coefficient of elasticity of trading (CET) as a measure of liquidity using Nigerian stock market data. Given that liquidity is multidimensional, the CET is complemented with the popular measure of liquidity, turnover ratio to explore the causal relationship among the CET, turnover ratio and market return to determine their relevance in security valuation. In other words, an attempt is made to examine if either of these two measures of liquidity is a relevant factor in explaining stock market return.

The Toda-Yamamoto version of Granger causality test is applied to two sets of data on the Nigerian Stock Exchange (NSE). The available monthly time series data are from 2008 to 2019 while the annual data are from 1986 to 2018. The Toda-Yamamoto test is preferred because it is more robust to integration and cointegration of the variables.

The results of the Toda-Yamamoto version of the Granger causality test on monthly data reveal no causal relationship between CET and market return, turnover and market return and CET with turnover and market return. These results are consistent with those for several frontier countries reported by Rubio et al. (2005), Hartian and Sitorus (2015), Batten and Vo (2019) and Sterenczak et al. (2020). The results support the conclusion that the Nigerian economy is not fully integrated with the global economy. Market inefficiency due to order imbalances given the nature of the trading system can also explain the reported results. However, the results from annual data do not tally with the monthly results. There is causality running from CET to market return. There is also causality running from turnover to market return. Therefore, both CET and turnover are statistically significant causal predictors of market return. The results from annual data are consistent with those reported by Marozva (2019).

The key limitation is availability of high-frequency transaction-level data to researchers to consider many measures of liquidity that have been employed in developed countries. The research implication is that more researchers will be encouraged to conduct more studies on liquidity and how the study results can drive policy recommendations. The standard asymptotic distribution of underlying the Toda-Yamamoto approach has been found to lead to overrejection.

This study is the first to apply Toda-Yamamoto model on data from Nigeria to investigate the causal relationship between stock market return and liquidity proxied by the CET given the nature of the automated trading system (ATS) in use. The CET is also complemented with the turnover ratio to explore the multidimensional nature of liquidity and its causal relationship with market return. The study is also interpreted as a determination of the integration of Nigeria's economy with the global economy with its implication on investment diversification.