Search results

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.