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The aim of this paper is to develop an approach for identifying the optimal level of automation by maximizing the level of automation and accuracy while addressing problem areas of forecast quality.

We use a unique set of forecasts planned by six subsidiaries of a multinational corporation to train and test various models. We compare the accuracy of three levels of automation and how they address prevalent forecasting process quality problem areas.

The findings indicate that accuracy alone is not a sufficient dimension to consider when selecting the optimal level of automation but that forecast process quality areas need to be assessed as well.

The limitations of this work are the inability to study the effects of our tool’s recommendations, the sample originating from a single company, the use of simple statistical methods and the limited number of dimensions to evaluate forecasts.

Firms should apply the structure offered in this paper to target individual components of the cash flow forecasting process when automating it and use it to structure their discussion, planning and implementation of automation.

A novel approach for determining the optimal level of automation for cash flow forecasting combining the human information processing framework of Parasuraman et al. (2000) with the forecast quality problem areas by Fildes and Petropoulos (2015).

On 20 April ISHM‐Benelux held its 1988 Spring meeting at the Grand Hotel Heerlen. This meeting was totally devoted to implantable devices, in particular to the technologies used for these high reliability, extremely demanding devices. For this meeting ISHM‐Benelux was the guest of the Kerkrade facility of Medtronic. Medtronic (headquartered in Minneapolis, USA) is the world's leading manufacturer of implantable electronic devices. Apart from the assembly of pacemakers and heart‐wires, the Kerkrade facility acts as a manufacturing technology centre for Medtronic's European facilities.

Particularly in volatile, uncertain, complex and ambiguous (VUCA) business conditions, staff in supply chain management (SCM) look to real-time (RT) data processing to reduce uncertainties. However, based on the premise that data processing can be perfectly mastered, such expectations do not reflect reality. The purpose of this paper is to investigate whether RT data processing reduces SCM uncertainties under real-world conditions.

Aiming to facilitate communication on the research question, a Delphi expert survey was conducted to identify challenges of RT data processing in SCM operations and to assess whether it does influence the reduction of SCM uncertainty. In total, 14 prospective statements concerning RT data processing in SCM operations were developed and evaluated by 68 SCM and data-science experts.

RT data processing was found to have an ambivalent influence on the reduction of SCM complexity and associated uncertainty. Analysis of the data collected from the study participants revealed a new type of uncertainty related to SCM data itself.

This paper discusses the challenges of gathering relevant, timely and accurate data sets in VUCA environments and creates awareness of the relationship between data-related uncertainty and SCM uncertainty. Thus, it provides valuable insights for practitioners and the basis for further research on this subject.

The purpose of this paper is to examine the incidence of public education subsidies in Ghana. Since the late 1990s, Ghana’s government has increasingly recognized human capital as key to alleviating poverty and income inequality, causing dramatic increases of government expenditures to the education sector. At the same time user fees have been introduced in higher education while basic education is being made progressively free. The question then is, whether these spending increases have been effective in reaching the poor and to what extent? What factors influence the poor’s participation in the public school system?

The authors address the key issues by employing both the standard benefit incidence methods and the willingness-to-pay method.

The results give a clear evidence of progressivity with consistent ordering: pre-schooling and primary schooling are the most progressive, followed by secondary, and then tertiary. Own price and income elasticities are higher for private schools than public schools and for secondary than basic schools.

Given the liquidity constraints African governments face yet there is the need to improve the human capacity of the countries, this study offers solution to how to optimally allocate the educational budget.

The use of policy simulations to ascertain the incidence of public spending on education is innovative as far as previous studies in Africa is concerned.

The use of modern technologies of the fourth industrial revolution, commonly known as “Industry 4.0” (I4.0), is believed to have considerable potential for product customisation. In this context, this paper aims to explore whether or not using these technologies impacts customer participation (CP) in a firm's new product development (NPD) process.

To empirically test the proposed relationships, the authors collected the North Italian manufacturing firms' data and applied regression analysis.

Empirical results indicate that, on the one hand, the technologies have their specific and individual impacts, and on the other hand, the firms which use more I4.0 technologies allow more customer participation in their product design and production process. This positive impact is more robust in product design than in the production process.

Managers aiming to benefit from CP should broaden the scope of adopting I4.0 technologies and consider different roles concerning the design and production phases of the new product development process. Recognising the importance and allowing CP in NPD will enable firms to meet the customised demands.

To the best of the authors' knowledge, the proposed relationships of this study have been extensively debated theoretically in the I4.0 context but never empirically tested before. It is one of the few studies which discusses the strategic adoption and the combined use of I4.0 technologies to create more opportunities for product customisation.

The purpose of this manuscript is to provide a step-by-step primer on systematic and meta-analytic reviews across the service field, to systematically analyze the quality of meta-analytic reporting in the service domain, to provide detailed protocols authors may follow when conducting and reporting these analyses and to offer recommendations for future service meta-analyses.

Eligible frontline service-related meta-analyses published through May 2021 were identified for inclusion (k = 33) through a systematic search of Academic Search Complete, PsycINFO, Business Source Complete, Web of Science, Google Scholar and specific service journals using search terms related to service and meta-analyses.

An analysis of the existing meta-analyses within the service field, while often providing high-quality results, revealed that the quality of the reporting can be improved in several ways to enhance the replicability of published meta-analyses in the service domain.

This research employs a question-and-answer approach to provide a substantive guide for both properly conducting and properly reporting high-quality meta-analytic research in the service field for scholars at various levels of experience.

This work aggregates best practices from diverse disciplines to create a comprehensive checklist of protocols for conducting and reporting high-quality service meta-analyses while providing additional resources for further exploration.

Mobile e-commerce has brought convenience to consumers. But for goods such as shoes, mobile e-commerce has failed to provide the same experience as consumers would have in physical stores, and that also causes problems for online merchants, such as high return rates. As a result, the augmented reality (AR) virtual shoe-try-on function appeared. The way that AR virtual shoe-try-on study different from other AR virtual try-on studies is that AR virtual shoe-try-on study only satisfies consumers' visual experience and consumers cannot judge whether the shoes are comfort or not. Whether consumers would accept AR virtual try-on function to help them make purchase decision due to the visual experience provided by AR virtual try-on function is worth discussion. Measuring users' perceptions and preferences can help companies design AR shoe-trying functions and provide services more cost-effectively.

To promote the continuous use and better development of such mobile e-commerce based on the technology acceptance model (TAM), this study explored the influencing factors for users' intentions to continue using the AR virtual shoe-try-on function, including the perceived usefulness, perceived ease of use, system quality, perceived playfulness and attitude.

The results of this study showed that TAM is a powerful theoretical tool of the new technology in mobile e-commerce and that the system quality and perceived playfulness also have a positive impact on the original variables of TAM. System quality and perceived playfulness are important predictors of users' continuance intentions to use the AR virtual shoe-try-on function.

The main contribution of this study to model iteration and theoretical update is to verify the applicability of the TAM in the AR shoe-try-on function and to expand TAM model with system quality and perceived playfulness. The authors' results will help shoe enterprises win users' recognition through AR shoe-try-on function and improve users' continuance intention of use.