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The purpose of this paper is to identify, study and quantify the effects of lighting on yield and productivity in manual electronics assembly (MEA) and inspection as a limiting work design criterion. The study also examines the potential interactions among lighting option, workers' age, and years of experience.

A three‐factor full factorial experiment is adopted to statistically evaluate the independent variables (process yield and assembly time) versus randomly selected levels of three factors: type of light (low pressure sodium, mercury vapor lamps, and metal halide lamps measured in foot‐candle luminaries), operator age, and years on the job. A residual analysis is also conducted to complement and corroborate the ANOVA findings.

The study finds that metal halide lamps, based on the ANSI recommended ranges of 186‐464 foot‐candles, lead to significant increases in labor productivity and through‐put, irrespective of operators' age and years of experience. Although these lamps have a significantly shorter life span than that of low‐pressure sodium and mercury vapor lamps, the realized benefits far exceed the incremental cost of illumination devices. The results indicate that a modest capital investment is able to generate solid improvements in yield and processing time in a typical MEA environment.

The relations between productivity and lighting intensity and type have never been studied in the area of MEA. This empirical study uncovers the effects through a systematic experimentation of this essential relationship in a typical MEA environment. The findings, which can be generalized to other facilities, are validated by an array of statistical procedures and proved to be significant. The paper contributes useful knowledge to the fields of engineering management and facility design.

Demand forecasting has long been an imperative tenet in production planning especially in a make-to-order environment where a typical manufacturer has to balance the issues of holding excessive safety stocks and experiencing possible stockout. Many studies provide pragmatic paradigms to generate demand forecasts (mainly based on smoothing forecasting models.) At the same time, artificial neural networks (ANNs) have been emerging as alternatives. In this chapter, we propose a two-stage forecasting approach, which combines the strengths of a neural network with a more conventional exponential smoothing model. In the first stage of this approach, a smoothing model estimates the series of demand forecasts. In the second stage, general regression neural network (GRNN) is applied to learn and then correct the errors of estimates. Our empirical study evaluates the use of different static and dynamic smoothing models and calibrates their synergies with GRNN. Various statistical tests are performed to compare the performances of the two-stage models (with error correction by neural network) and those of the original single-stage models (without error-correction by neural network). Comparisons with the single-stage GRNN are also included. Statistical results show that neural network correction leads to improvements to the forecasts made by all examined smoothing models and can outperform the single-stage GRNN in most cases. Relative performances at different levels of demand lumpiness are also examined.

The purpose of this paper is to explore two identified knowledge gaps: first, the identification and analysis of online searching trends for Financial Technology (FinTech)-related jobs and education information in UK, and second to assess the current strength of the FinTech-related job distribution in terms of job titles and locations in UK, job market in UK and what is required to help it to grow.

Two sets of data were used in this study in order to fill the two identified knowledge gaps. First, six years’ worth of data, for the period from September 2012 to August 2018 was collected from Google Trends. This was in the form of search term keyword text. The hypothesis was designed correspondingly, and the results were reviewed and evaluated using a relevant statistical tool. Second, relevant data were extracted from the “Indeed” website (www.indeed.co.uk) by means of a simple VBA programme written in Excel. In total, the textual data for 500 job advertisements, including the keyword “FinTech”, were downloaded from that website.

The authors found that there was a continuously increasing trend in the use of the keyword “fintech” under the category “Jobs and Education” in online searching from September 2012 to August 2018. The authors demonstrated that this trend was statistically significant. In contrast, the trends for searches using both “finance” and “accounting” were slightly decreased over the same period. Furthermore, the authors identified the geographic distribution of the fintech-related jobs in the UK. In regard to job titles, the authors discovered that “manager” was the most frequently searched term, followed by “developer” and “engineer”.

Educators could use this research as a reference in the development of the portfolio of their courses. In addition, the findings from this study could also enable potential participators to reflect on their career development. It is worth noting that the motivations for carrying out an internet search are complex, and each of these needs to be understood. There are many factors that would affect how an information seeker would behave with the obtained information. More work is still needed in order to encourage more people to enter to the FinTech sector.

In the planning stage prior to launching a new course educators often need to justify the market need: this analysis could provide a supporting rationale and enable a new course to launch more quickly. Consequently, the pipeline of talent supply to the sector would also be benefitted. The authors believe this is the first time that a study like this had been conducted to explore specifically the availability and opportunities for FinTech education and retraining in UK. The authors anticipate that this study will become the primary reference for researchers, educators and policy makers engaged in future research or practical applications on related topics.

Microlearning has been considered as a promising topic in work-based learning. This paper aims to review the trends of microlearning in terms of related publications and Internet searches. Hopefully, the findings can serve as a reference for the education sector, government, business and academia to promote, design and use microlearning.

In this study, two sets of analysis were conducted. Firstly, the authors analysed the publication trend of microlearning. Second, the authors analysed the trend of Internet searches related to microlearning. More specifically, the authors analysed real-world data of 14 years obtained from Scopus and Google Trends for the purpose. These data include the first relevant publication found in the database.

In total, 476 relevant publications have been identified during 2006–2019. According to the findings from the analysis of the identified publications, microlearning is a relevantly new and emerging global topic involving authors, affiliations and funding sponsors from different countries. Moreover, many microlearning-related publications were conducted from perspectives of e-learning or mobile learning. Furthermore, the authors notice higher education was the most frequently mentioned education level in the identified publications. On the other hand, language learning (i.e. second language, vocabulary learning, etc.) had been mentioned more times in the titles and abstracts than other subject areas. Overall, the increasing trend of publications on “microlearning” (as a knowledge supply) is in line with the established increasing Internet searches of “microlearning” (as a practical demand) in recent years.

From the work-based learning perspective, microlearning has been considered as one of the key topics in talent development topics. Policymakers, educators, researchers and participators have the responsibility to explore how to promote, design and use microlearning to help people to learn in the right direction through valid knowledge with ethical consideration.

Although many works had been done on microlearning, there is a lack of comprehensive studies reviewing the trends of microlearning in terms of related publications and Internet searches. This study aims to fill this gap by analysing real-world data obtained from Scopus and Google Trends – these data include the first relevant publication found in the database. The authors believe this is the first time that a study has been conducted to comprehensively review the development trends of microlearning. Hopefully, this study can shed some light on related research.

Despite great developments in silicon technology over the past decade, hybrid microelectronics continue to survive for a number of reasons. One reason is the difficulty of achieving acceptable component tolerances for resistors and capacitors in silicon. Another reason is the ability to trim resistors in thick film, which makes it more attractive for use in analogue circuits. Furthermore, if the volume of production is not high enough to justify a high non‐recurring expense (NRE), a hybrid circuit would be a feasible solution. The rediscovery of the advantages of multi‐chip modules (MCMs) will further boost the growth of the hybrid microcircuits market in the '90s. MCMs offer the advantages of high reliability, performance (high speed) and miniaturisation (size and weight). This paper briefly outlines the activities of certain government bodies and tertiary institutions in the field of microelectronics. Emphasis is given to the areas of activity where hybrid industry professionals may participate. Perceptions of trends in the '90s are explored in a way that should inspire and generate enthusiasm among microelectronics professionals.

Post-merger integration (PMI) success depends heavily on the social and cultural integration of the two legacy organizations. Given that organizational members work and exchange information through social relationships, social network analysis can serve as a useful tool to identify key actors, address areas of concern, and measure PMI success. However, few PMI studies have employed a social network perspective or social network analysis. In this chapter, the authors review the current literature on PMI and organizational change, including the few studies that use social networks approach. The authors also identify recent developments in social networks and organizational change research that can improve our understanding of PMI processes and propose promising avenues for future research. Further, the authors identify obstacles for social network research on PMI and provide practical advice for overcoming them.

This study identified essential drivers of competitive productivity (CP) within the restaurant context at the meso-micro levels. Following evidence from previous research, this paper aims to discover if the relationships between the proposed drivers and restaurant competitive productivity (RCP) would differ based upon years in operations as a restaurant business (startup vs established).

Data analysis was conducted using responses obtained from US restaurant managers. Structural equation modeling assessed the hypothesized relationships. Additionally, multi-group analyses were conducted to test the proposed moderating roles of restaurant firm age within the proposed model.

Results documented that competitive personality, development and motivation were positively associated with employee competitive productivity (ECP) at the micro-level. Also, ECP, employee training, resource rareness, brand image and organizational culture were significantly and positively related to RCP at the meso-level. Additionally, the positive relationships between ECP and organizational culture, and RCP were greater in the established restaurant group compared with the startup group. However, the relationship between brand image and RCP was greater in the restaurant startup group than in the established group.

This study offered empirical evidence regarding a combination of meso and micro level drivers and their roles in improving RCP. Findings can be adopted to develop effective operational strategies to improve RCP.

Although RCP is critical and is proposed to be created by a comprehensive set of drivers considering organizational (meso-) and individual (micro-) situations, no literature has yet to adopt this comprehensive approach to assess RCP. This study focused on firm age and offered new knowledge about the need for developing specific strategies to improve RCP.