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The purpose of this paper is to examine how a Ghanaian migrant family business in Kent makes financial decisions and measures business growth within the framework of Social Network theory and focussing on influences such as family, cultural and social factors.

Case study: migrant Ghanaian family business owner in Kent, first generation who migrated to the UK after the year 2000. The business is a small and medium enterprise and running the business as a family.

The narrative highlights important aspects of cultural and social factors that are not usually considered in credit analysis or applications for a relationship with a mainstream financial services institution. It is also indicated that family and personal attributes and culture had the most social capital for the shop owner to use or explore in taking her financial decisions. The discussions provide a basic framework for future research.

There is a gap in the research of Ghanaian migrant family businesses in the UK, in particular of their financial decision making process.

This study investigates how education, scientific output, and the internet complement mobile phone penetration to affect technology commodity exports in sub-Saharan Africa for the period 2000–2012. The empirical evidence is based on a generalized method of moments. The following main findings are established. The internet complements the mobile phone to boost technology goods exports and technology service exports. In addition, positive marginal effects are apparent in the roles of educational quality and scientific output on technology goods exports and technology service exports, respectively, while negative marginal impacts are apparent in the roles of scientific output and educational quality on technology goods exports and technology service exports, respectively. Practical and theoretical implications are discussed.

In this chapter, we document the growing importance of FDI from BRIC countries in relation to FDI from both developed and developing countries and investigate the types of firms that are responsible for BRIC FDI.

We follow a two-step empirical approach. First, we provide macro evidence on FDI from BRIC countries. We use UNCTAD data to highlight the patterns of FDI flows and stocks. Second, we provide firm-level evidence on FDI. Using ORBIS data, we elaborate a rich taxonomy of FDI that accounts for the decision to invest abroad and for the location, ownership, and number of foreign subsidiaries. Thus, we characterize BRIC multinationals’ involvement in FDI and examine the relationship between FDI and performance at the firm level.

We unveil new facts about BRIC multinationals. BRIC multinationals are in the minority in their home countries, but they outperform domestic enterprises. Within the group of BRIC investors, those firms that invest in developing countries, that operate in joint ventures, or that have more than five foreign subsidiaries are in the minority, but they outperform those firms that select other FDI strategies.

Our estimates document a positive and robust correlation between FDI and performance; however, the cross-sectional nature of our data does not permit a proper causality analysis.

Our work contributes to the International Economics literature on internationalization and firm performance as well as to the International Business literature on FDI from emerging economies. With respect to the former, we innovate by studying the relation between FDI strategies and firm performance. In relation to the latter, we innovate by introducing firm-level data and a cross-country approach that lets us illustrate the roles and features of FDI from BRIC countries.

The purpose of this paper is to examine the way serial correlation in quarterly earnings forecast errors varies with firm and analyst attributes such as the firm’s industry and the analyst’s experience and brokerage house affiliation. Prior research on financial analysts’ quarterly earnings forecasts has documented serial correlation in forecast errors.

Finding that serial correlation in forecast errors is significant and seemingly independent of firm and analyst attributes, the consensus forecast errors are modeled as an autoregressive process. The model of forecast errors that best fits the data is AR(1), and the obtained autoregressive coefficients are used to predict consensus forecast errors.

Modeling the consensus forecast errors as an autoregressive process, the present study predicts future consensus forecast errors and proposes a series of refinements to the consensus.

These refinements were not presented in prior literature and can be useful to financial analysts and investors.

User-generated social media comments can be a useful source of information for understanding online corporate reputation. However, the manual classification of these comments is challenging due to their high volume and unstructured nature. The purpose of this paper is to develop a classification framework and machine learning model to overcome these limitations.

The authors create a multi-dimensional classification framework for the online corporate reputation that includes six main dimensions synthesized from prior literature: quality, reliability, responsibility, successfulness, pleasantness and innovativeness. To evaluate the classification framework’s performance on real data, the authors retrieve 19,991 social media comments about two Finnish banks and use a convolutional neural network (CNN) to classify automatically the comments based on manually annotated training data.

After parameter optimization, the neural network achieves an accuracy between 52.7 and 65.2 percent on real-world data, which is reasonable given the high number of classes. The findings also indicate that prior work has not captured all the facets of online corporate reputation.

For practical purposes, the authors provide a comprehensive classification framework for online corporate reputation, which companies and organizations operating in various domains can use. Moreover, the authors demonstrate that using a limited amount of training data can yield a satisfactory multiclass classifier when using CNN.

This is the first attempt at automatically classifying online corporate reputation using an online-specific classification framework.

This study aims to confirm earlier findings that differences between merger and acquisition (M&A) participant firms are a hurdle for successful mergers and shows that merger outcomes can also be affected by the post-merger integration duration (PMID).

Experimental research on distinct cultures developed within experimental pre-merger subject groups is used to compare pre- and post-integration performances.

This study finds that firm distance (i.e. inherent differences between pre-merger firms) negatively influences merger success; no significant relationship between firm distance and PMID exists and PMID is positively related to merger success. Specifically, a slower integration minimizes conflicts between merger partners, enhances trust-building and reduces the disruption of existing resources and processes in both firms, which may benefit M&As. By contrast, a fast integration that shortens the overall integration process may discourage the combined entity from recognizing the intended synergy quickly.

The new finding that PMID can affect merger outcomes invites empirical validation. This study presents experimental evidence that prolonged, well-structured post-merger integration may compensate for the negative time-variant issues associated with PMID.

Organizational support for collaborative learning between professional members should be a strategic consideration for firms so that acquiring business capabilities can be more natural and cost-efficient than building internal capabilities despite possibly slowing down the integration process. Encouraging a transfer of technical and client knowledge between the combined members can create value and understand differences in both the form and content of each firm’s knowledge base and the pre-existing mechanisms for sharing knowledge. It may lower the level of resistance in knowledge transfer.

While M&As may better facilitate the cost-effective expansion of business offerings than building capabilities internally, they can require considerable time, preventing many firms from realizing their intended outcomes. Nevertheless, less attention has been focused on PMID and its influence on M&As. This study is the first to use experimental research to examine the effects of PMID on merger success.

This study investigates how enhancing information and communication technology (ICT) affects female economic participation in sub-Saharan African nations.

Three female economic participation indicators are used, namely female labour force participation, female unemployment and female employment rates. The engaged ICT variables are fixed broadband subscriptions, mobile phone penetration and Internet penetration. The Generalized Method of Moments is used for the empirical analysis.

The following main findings are established: First, there is a (1) negative net effect in the relevance of fixed broadband subscriptions in female labour force participation and female unemployment and (2) positive net effects from the importance of fixed broadband subscriptions on the female employment rate. Secondly, an extended analysis is used to establish thresholds at which the undesirable net negative effect on female labour force participation can be avoided. From the corresponding findings, a fixed broadband subscription rate of 9.187 per 100 people is necessary to completely dampen the established net negative effect. Hence, the established threshold is the critical mass necessary for the enhancement of fixed broadband subscriptions to induce an overall positive net effect on the female labour force participation rate.

This study complements the extant literature by assessing how increasing penetration levels of ICT affect female economic inclusion and by extension, thresholds necessary for the promotion of ICT to increase female economic inclusion.

Chapter 2 offers examples of colonial and neocolonial working throughout history. This chapter defines and provides an overview of colonialism’s development and its economic and administrative roots. This chapter is intended to contextualize colonialism rather than explain its complete history.

Prior studies suggest that, in an industry in which several public firms operate (i.e. greater public firm presence), uncertainty about business operations within the industry is reduced due to greater analyst coverage and quality of information disclosure. In this study, the authors examine how UK private firms respond to investment opportunities in fixed intangible assets (FIAs) in an environment characterised by greater public firm presence (PFP).

Using data from 61,278 (1,358) private (public) UK firms operating in ten sectors spanning from 2006 to 2016, the authors conduct this analysis by using panel econometric techniques.

The authors observe that private firms are more responsive to their FIA investment opportunities when they operate in industries with more PFP. Also, the authors find that firms in industries with better information quality use more debt and have longer debt maturity security but less internal cash flow. Overall, the findings indicate that PFP generates positive externalities for private firms by lessening industry uncertainty and enhancing more efficient FIA investment. The results are robust to endogeneity concerns.

A key limitation of the study is that it focuses on a single country (the UK) and therefore there is a likelihood that the results found are specific to this setting but not others, particularly developing and emerging economies. Thus, future studies could explore these ideas from the viewpoint of multiple countries.

Overall, the study demonstrates the importance of information disclosure in driving investment decisions of firms.

While this paper builds on the information disclosure and corporate investment literature, it is one of the first attempts, to the best of the authors’ knowledge, to explore how private UK firms respond to investment in FIAs in an environment characterised by greater PFP.