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Robotic process automation (RPA) has recently emerged as a technology focusing on the automation of repetitive, frequent, voluminous and rule-based tasks. Despite a few practical examples that document successful RPA deployments in organizations, evidence of its economic benefits has been mostly anecdotal. The purpose of this paper is to present a step-by-step method to RPA investment appraisal and a business case demonstrating how the steps can be applied to practice.

The methodology relies on design science research (DSR). The step-by-step method is a design artefact that builds on the mapping of processes and modelling of the associated costs. Due to the longitudinal nature of capital investments, modelling uses discounted cashflow and present value methods. Empirical grounding characteristic to DSR is achieved by field testing the artefact.

The step-by-step method is comprised of a preparatory step, three modelling steps and a concluding step. The modelling consists of compounding the interest rate, discounting the investment costs and establishing measures for comparison. These steps were applied to seven business processes to be automated by the case company, Estate Blend. The decision to deploy RPA was found to be trivial, not only based on the initial case data, but also based on multiple sensitivity analyses that showed how resistant RPA investments are to changing circumstances.

By following the provided step-by-step method, executives and managers can quantify the costs and benefits of RPA. The developed method enables any organization to directly compare investment alternatives against each other and against the probable status quo where many tasks in organizations are still carried out manually with little to no automation.

The paper addresses a growing new domain in the field of business process management by capitalizing on DSR and modelling-based approaches to RPA investment appraisal.

The purpose of this study is to understand the profit implications of analytics-driven centralized discriminatory pricing at the headquarter level compared with sales force price delegation in the purchase of an aftermarket good through an indirect retail channel with symmetric information.

Using individual-level loan application and approval data from a North American financial institution and segment-level customer risk as the price discrimination criterion for the firm, the authors develop a three-stage model that accounts for the salesperson’s price decision within the limits of the latitude provided by the firm; the firm’s decision to approve or not approve a sales application; and the customer’s decision to accept or reject a sales offer conditional on the firm’s approval. Next, the authors compare the profitability of this sales force price delegation model to that of a segment-level centralized pricing model where agent incentives and consumer prices are simultaneously optimized using a quasi-Newton nonlinear optimization algorithm (i.e. Broyden–Fletcher–Goldfarb–Shanno algorithm).

The results suggest that implementation of analytics-driven centralized discriminatory pricing and optimal sales force incentives leads to double-digit lifts in firm profits. Moreover, the authors find that the high-risk customer segment is less price-sensitive and firms, upon leveraging this segment’s willingness to pay, not only improve their bottom-line but also allow these marginalized customers with traditionally low approval rates access to loans. This points out the important customer welfare implications of the findings.

Substantively, to the best of the authors’ knowledge, this paper is the first to empirically investigate the profitability of analytics-driven segment-level (i.e. discriminatory) centralized pricing compared with sales force price delegation in indirect retail channels (i.e. where agents are external to the firm and have access to competitor products), taking into account the decisions of the three key stakeholders of the process, namely, the consumer, the salesperson and the firm and simultaneously optimizing sales commission and centralized consumer price.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.

This study explores the contribution of social entrepreneurship to the realization of the Sustainable Development Goals (SDGs) in Uganda.

We employed a qualitative approach and a multiple-case design to engage 20 participants. Specifically, semi-structured interviews were conducted to gather the perceptions and views of the participants regarding the study phenomenon.

Study findings indicate that social entrepreneurs support a number of people and undertake activities that solve social, environmental and economic problems. However, environmental issues receive less focus when compared to other sustainability aspects. It is also evident that social entrepreneurs are financially constrained with limited managerial skills, undermining their potential to fulfill their social mission. Despite these challenges, social entrepreneurs have significantly contributed to the attainment of SDGs 1, 4, 5, 8 and 10 in Uganda.

This study contributes to the existing literature on social entrepreneurship and sustainable development. Specifically, it provides initial empirical evidence on the social entrepreneurial activities, the beneficiaries and challenges being addressed by social entrepreneurs and contribution to the attainment of the SDGs in Uganda.

This research explores the intricate dynamics of national interests realised through Japan's official development assistance (ODA) to China. It aims to deepen the understanding of these mechanisms, detailing the extent to which Japan has accomplished its national interests.

The paper applies the role theory and narrative analysis to elucidate Japan's national role conception and its categories of national interests with regards to its ODA policy. It utilises both qualitative and quantitative methods to examine the success rate in achieving Japan's diplomatic objectives and how those interests have manifested over time.

The findings suggest a mixed outcome. Whilst Japan's ODA to China has helped in expanding trade and fostering mutual understanding and cooperation, it has been less successful in promoting democratic governance in China or effectively counterbalancing China's regional power. Hence, the realisation of national interests through ODA is a complex process contingent upon numerous factors.

This study stands out for its multifaceted approach in examining Japan's ODA policy towards China, integrating both quantitative and qualitative methodologies and applying the role theory in the context of international development aid. It fills a significant gap in the literature by analysing the interplay between national interests and foreign aid, providing nuanced insights into the successes and challenges of Japan's pursuit of its diplomatic objectives. The study's findings have important implications for understanding the complexity of international aid dynamics and can inform future policy decisions in the realm of international relations and foreign aid.

The Polish economy has undergone major challenges and changes over the past few decades. The country's trade flows, in particular, have become more firmly tied to the country’s Western neighbors as they have grown in volume. This study examines Poland's trade balances in ten Standard International Trade Classification (SITC) sectors versus the United States of America, first testing for and isolating structural breaks in each time series. These breaks are then included in a set of the cointegration models to examine their macroeconomic determinants.

Linear and nonlinear and nonlinear autoregressive distributed lag models, both with and without dummies corresponding to structural breaks, are estimated.

One key finding is that incorporating these breaks reduces the significance of the real exchange rate in the model, supporting the hypothesis that this variable already incorporates important information. It also results in weaker evidence for cointegration of all variables in certain sectors.

This study looks only at one pair of countries, without any third-country effects.

An important country pair's trade relations is examined; in addition, the real exchange rate is shown to incorporate economic information that results in structural changes in the economy. The paper extends the existing literature by conducting an analysis of Poland's trade balances with the USA, which have not been studied in such a context so far. A strong point is a broad methodology that lets compare the results the authors obtained with different kinds of models, both linear and nonlinear ones, with and without structural breaks.

The integration of the digital economy and the real economy has been a key focus in promoting digital economic development. It denotes a comprehensive digital transformation of national economic activities regarding technological infrastructure and production modes, which is crucial for establishing a modern economic system, advancing industrial infrastructure and modernizing industrial chains.

Firstly, the study delves into the internal logic behind the emergence of the new development dynamic resulting from digital technology's evolution. Secondly, it explores the mechanism of mutual promotion and support between the new development dynamic and the digital economy based on China's shift in focus from international engagement to the domestic economy during different stages of industrialization. Subsequently, it analyzes the characteristics and critical factors of digital economy development and examines the macro-, meso- and micro-level constraints on these factors. Finally, the paper explores approaches to promoting digital economy development while constructing the new development dynamic and provides relevant policy suggestions.

The construction of the new development dynamic and the development of the digital economy are inextricably linked, and only by mutually reinforcing each other can they provide an inexhaustible impetus for China's high-quality economic development.

The new development dynamic and the digital economy development form an indivisible whole. The new development dynamic creates the necessary conditions for digital economy development and promotes the formation of digital production modes. In turn, the development of the digital economy should strive to improve the mainstay position of the domestic economy, enhance the synergy between the domestic economy and international engagement, upgrade value chains while improving the supply and the industrial chains in China and ensure a parallel increase in labor income alongside improved productivity.

This paper investigates the effect of state-society relations on the industrially-related growth paths of developed countries.

It introduces a novel theoretical framework, the state-business-labor relations (SBLR) framework, where four main actors are identified: the state, big businesspersons or tycoons, owners and managers of small and medium enterprises (SMEs) or Entrepreneurs and labor. Different SBLR categories or modes are introduced depending on levels of coordination and power relations between the studied actors. The paper then investigates how these SBLR modes, through adopting various policies targeting the industrial sector, lead to different growth paths. Rather than focusing only on economic growth, this research regards a growth path as a matrix of the performance in long-run growth and equality of distribution.

Using regression analysis and statistical data, the results suggest that the Co-Balanced mode, having higher levels of coordination and lower favoritism, leads to the best growth path among the four introduced modes, especially with its emphasis on high levels of venture capital availability and easiness of starting business. while the Lib-Capture mode, characterized by lower coordination and higher favoritism, seems to have the worst growth path and the best implemented policy for this mode is suggested to be high profit taxes that seem to counter the negative impact of the existing high levels of favoritism.

Despite the important findings that this research has reached, this paper is mainly meant to open a further investigation into this topic and open this dimension that the research on VoC and political economy have under-researched. A deeper investigation of SBLR typologies that could only be possible by having richer datasets with more data on coordination for the whole world, rather than only the advanced economies, would further our understanding of the dynamics that shape the growth paths of different countries of the world.

To realize the best industrial growth path, fighting favoritism should be an important objective. The negative impact of favoritism on innovation could not be disregarded in the eve of the fourth industrial revolution, where innovation is increasingly pivotal to future industrial development. Actively engaging societal groups in the policymaking process is important in addressing their concerns and balancing them at the same time. This should lead to the double benefit of formulating better policies that should foster growth as well as provide better distribution of this growth. High levels of coordination should help in realizing this objective. Yet, this could only be possible if societal groups are free to associate and aggregate their power and when there are means of preventing one actor from gaining more favorite treatment and exclusive influence over policymakers. The presence of both powerful and broadly represented business associations and labor unions and the existence of a government interested in coordinating their efforts-rather than letting itself be controlled by one group at the expense of the others-should help in the realization of the best growth path. Thus, institutional reform that empowers societal groups and enables them to defend their interests as well as fights all forms of corruption should lead to the realization of a more prosperous and equitable industrial development, with the “re-industrialization” of the developed world being no exception. The technological and social challenges of intensive automation and digitalization accompanying the fourth industrial revolution make the envisaged institutional reform more urgent.

This paper is introducing a novel theoretical framework for studying the effect of state-society relations, particularly SBLR, on the industrial growth paths of developed countries. It integrates three important bodies of literature in order to build a more comprehensive understanding of the dynamics of state-society relations and their economic consequences. These are the Varieties of Capitalism (VoC), State-Business Relations (SBR) and Industrial Relations. The SBLR framework differentiates between tycoons and entrepreneurs, an important distinction that often goes unnoticed. Different SBLR categories or modes are introduced, depending on levels of coordination and power relations between the actors. It is proposed in this research that the effect on growth paths goes beyond the simple dichotomy between CMEs and LMEs usually present in the literature of VoC and that power relations provide an essential complementary dimension in explaining this causality.

In this paper we examine the validity of the J-curve hypothesis in four Southeast Asian economies (Indonesia, Malaysia, the Philippines and Thailand) over the 1980–2017 period.

We employ the linear autoregressive distributed lags (ARDL) model that captures the dynamic relationships between the variables and additionally use the nonlinear ARDL model that considers the asymmetric effects of the real exchange rate changes.

The estimated models were diagnostically sound, and the variables were found to be cointegrated. However, with the exception of Malaysia, the short- and long-run relationships did not attest to the presence of the J-curve effect. The trade flows were affected asymmetrically in Malaysia and the Philippines, suggesting the appropriateness of nonlinear ARDL in these countries.

The previous research tended to examine the effects of the real exchange rate changes on the agricultural trade balance and specifically the J-curve effect (deterioration of the trade balance followed by its improvement) in the developed economies and rarely in the developing ones. In this paper, we address this omission.

This paper aims to investigate the determinants of global interest in central bank digital currency (CBDC). It assessed whether global interest in sustainable development and cryptocurrency are determinants of global interest in CBDC.

Google Trends data were analyzed using two-stage least square regression estimation.

There is a significant positive relationship between global interest in sustainable development and global interest in CBDC. There is a significant positive relationship between global interest in cryptocurrency and global interest in the Nigeria eNaira CBDC. There is a significant negative relationship between global interest in CBDC and global interest in the eNaira CBDC. There is a significant positive relationship between global interest in CBDC and global interest in the China eCNY. There is a significant negative relationship between global interest in cryptocurrency and global interest in the Sand Dollar and DCash.

The literature has not empirically examined whether global interest in sustainable development and cryptocurrency are factors motivating global interest in CBDC. This study fills a gap in the literature by investigating whether global interest in sustainable development and cryptocurrency are factors motivating global interest in CBDC.