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The purpose of this paper is to study the unit train make-up scheme for loaded direction in the heavy haul railway.

A 0-1 nonlinear integer programming model with the aim of minimizing the idling period between actual train arrival time and expected train arrival time for all loaded unit trains are proposed.

The proposed model is applied into a case study based on Daqin heavy haul railway. Results show that the proposed model can offer operators an optimal unit train make-up scheme for loaded direction in heavy haul railway.

The proposed model can offer operators an optimal unit train make-up scheme for loaded direction in heavy haul railway.

The purpose of this paper is to examine peer-to-peer sharing platform business models, their sources of competitive advantage, and the roles, motivations and behaviors of key actors in their ecosystems.

This paper uses a conceptual approach that is rooted in the service, tourism and hospitality, and strategy literature.

First, this paper defines key types of platform business models in the sharing economy anddescribes their characteristics. In particular, the authors propose the differentiation between sharing platforms of capacity-constrained vs capacity-unconstrained assets and advance five core properties of the former. Second, the authors contrast platform business models with their pipeline business model counterparts to understand the fundamental differences between them. One important conclusion is that platforms cater to vastly more heterogeneous assets and consumer needs and, therefore, require liquidity and analytics for high-quality matching. Third, the authors examine the competitive position of platforms and conclude that their widely taken “winner takes it all” assumption is not valid. Primary network effects are less important once a critical level of liquidity has been reached and may even turn negative if increased listings raise friction in the form of search costs. Once a critical level of liquidity has been reached, a platform’s competitive position depends on stakeholder trust and service provider and user loyalty. Fourth, the authors integrate and synthesize the literature on key platform stakeholders of platform businesses (i.e. users, service providers, and regulators) and their roles and motivations. Finally, directions for further research are advanced.

This paper helps platform owners, service providers and users understand better the implications of sharing platform business models and how to position themselves in such ecosystems.

This paper integrates the extant literature on sharing platforms, takes a novel approach in delineating their key properties and dimensions, and provides insights into the evolving and dynamic forms of sharing platforms including converging business models.

The purpose of this paper is to analyze why people have become suppliers in the sharing economy (SE) as Uber drivers in a developing country.

From a background on SE, car sharing and gig economy, the authors carried out a qualitative research. The analysis was based on 20 semi-structured interviews conducted with Uber drivers, and on the authors’ participant observation as Uber drivers and passengers in the third largest Brazilian city, Belo Horizonte.

Empirical evidence shows that becoming an Uber driver is more a matter of solving unemployment on a more permanent way rather than a search for a temporary and flexible work to supplement income. Although there are benefits related to flexibility, income and social interactions, negative externalities identified herein lead to the conclusion that the overall work relations and conditions are negative.

Much in the literature of the SE is focused on understanding consumer behavior; this research, on the contrary, is focused on understanding producers, which indicates an incipient perspective. The contributions of this paper show that the SE merges into different distributive decentralized means of production that are seeing as profit/income generated from shareable assets.

The purpose of this paper is to uncover the right type of organizational slack for innovation. It examines how city managers conceive slack, and how they create slack to facilitate innovation while dealing with fiscal stress.

The study is built around a comparative case study approach to uncover contrasts, similarities and patterns of slack-building for innovation in austere times. It relies on the experiences of 12 experienced city managers. Data are sought from elite interviews and one focus group.

The main finding is that innovation in the public sector does not benefit from slack in general, but from a specific type of slack. The evidence shows that useful slack for innovation is not so much about financial slack or HR slack, but about psychological slack.

This study adds to the literature that the key questions of slack research should not only focus on identifying the “right amount” of slack but also on identifying of the “right type” of slack.

Public managers who want to deal with (fiscal) crises more innovatively might reconsider their perceptions of slack and its value. Rather than operating on a pure cost effectiveness paradigm, they should balance the costs of slack and its innovative abilities.

This paper highlights the social/psychological side of austerity management. It concludes that increasing the ability of public organizations to innovatively cope with fiscal stress is not so much about increasing predictive capacity or financial buffers, but about increasing the mental leeway of coworkers.

One of the distinctive features in Korea and the U.S. trucking industries is the huge difference in the share of owner-operators. While it is around 10~15 percent in the U.S., 80~90% of drivers operate their own truck in Korea. Different from historical explanations of previous researches, this paper deals with this feature theoretically. We examine what brings the difference in asset ownership structures between the Korean and the U.S. trucking industries. Using an analytic framework, we investigate the determinants of truck ownership and the changes in ownership patterns. The model introduces several parameters related to productivities of drivers’ efforts and contractibility to affect drivers’ decision, and values of these parameters in both countries are discussed qualitatively and found to be consistent with the aforementioned characteristics.

Our study aims to evaluate the impact of infrastructure and public investment on private investment in machinery and equipment in Brazil from 1947 to 2017. The contribution of our article to the existing literature lies in providing a more comprehensive understanding of the presence or absence of the crowding effect in the Brazilian economy by leveraging an extensive historical database. Our central argument posits that the recent decline in private capital accumulation over the last few decades can be attributed to shifts in economic policies – moving from a developmentalist orientation to nondevelopmental guidance since the early 1990s, which is reflected in the diminished levels of public investment and infrastructure since the 1980s.

We conducted a series of econometric regressions utilizing the autoregressive distributed lag (ARDL) model as our chosen econometric methodology.

Employing two different variables to measure public investment and infrastructure, our results – robust across various specifications – have substantiated the existence of a crowding-in effect in Brazil over the examined period. Thus, we have empirical evidence indicating that the state has influenced private capital accumulation in the Brazilian economy over the past decades.

Our article contributes to the existing literature by offering a more comprehensive understanding of the crowding effect in the Brazilian economy, utilizing an extensive historical database.

The purpose of this paper is to review the current literature in the field of tourism demand forecasting.

Published papers in the high quality journals are studied and categorized based their used forecasting method.

There is no forecasting method which can develop the best forecasts for all of the problems. Combined forecasting methods are providing better forecasts in comparison to the traditional forecasting methods.

This paper reviews the available literature from 2007 to 2017. There is not such a review available in the literature.

Cloud Manufacturing (CM) is the manufacturing version of Cloud Computing and aims to increase flexibility in the provision of manufacturing services. On-demand manufacturing services can be requested by users to the cloud and this enables the concept of Manufacturing-as-a-Service (MaaS). Given the considerable number of prototypes and proofs of concept addressed in literature, this work seeks real CM platforms to study them from a business perspective, in order to discover what MaaS concretely means today and how these platforms are operating.

Since the number of real applications of this paradigm is very limited (if the authors exclude prototypes), the research approach is qualitative. The paper presents a multiple-case analysis of 6 different platforms operating in the manufacturing field today. It is based on empirical data and inductively researches differences among them (e.g. stakeholders, operational flows, capabilities offered and scalability level).

MaaS has come true in some contexts, and today it is following two different deployment models: open or closed to the provider side. The open architecture is inspired by a truly open platform which allows any company to be part of the pool of service providers, while the closed architecture is limited to a single service provider of the manufacturing services, as it happens in most cloud computing services.

The research shoots a picture of what MaaS offers today in term of capabilities, what are the deployment models and finally suggests a framework to assess different levels of development of MaaS platforms.

Although networked hospitality businesses as Airbnb are a recent phenomenon, a rapid growth has made them a serious competitor for the hospitality industry with important consequences for tourism and for tourist destinations. The purpose of this paper is to analyse the nature of the phenomenon, its potential further development in the next five years and the impact this developments will have on tourism, on hotels and on city destinations.

A literature study, combined with scenario workshops and a Delphi panel, were used to map current trends and uncertainties. With this input, future scenarios were elaborated using the Global Business Network (“scenario cross”) method.

Network platforms as Airbnb are often classified under something called the “Sharing Economy”, a denomination that obscures their true nature. Airbnb is a challenging innovation to which traditional hospitality will have to respond. Its impact has at the same time led to a call for regulatory policies. The definition of these policies and the evolution of tourism are variables that determine future scenarios. Attempts to ban the phenomenon mean a disincentive to innovation and protect oligopolistic markets; more receptive policies may have the desired results if tourism grows moderately but in booming destinations they may lead to a harmful commercialization.

Until now, Airbnb has been described in conceptual studies about the so-called “Sharing economy”, or more recently in empirical studies about isolated effects of holiday rentals. This paper contextualizes the evolution of networked hospitality and seeks to synthesize the sum of its impacts, thus enabling businesses and local governments to define positions and strategies.

Studies about product customization decision are especially relevant for organizations that decide opening a subsidiary overseas. This scenario requires the company to decide which products should be customized and which products should be standardized when selling products in international markets. The main purpose of this paper is to identify which factors influence the decisions on the customization of industrial products and consumer products to a particular country in the marketing function of a global company.

To do so, a literature review was conducted addressing the following topics: internationalization, international marketing and product customization factors. With regard to methodological aspects, an initial qualitative phase was conducted with four exploratory case studies. In the quantitative phase, an online survey was developed, obtaining 123 records of an intentional non-probabilistic sample.

As a result, six factors were deemed essential to the product customization decision: customers’ characteristics, sustainable return on investment, sustainable profit, legal requirements, sales of other products in the portfolio and weather differences.

The authors expect that the results of this research contribute academically for the management knowledge about the meanings that product customization can assume in internationalized companies, and, additionally, in a business way, the authors expect that they help companies make strategic decisions on the appropriate measure to take regarding product customization in international markets, whether industrial products or consumer products. With these findings, the authors expect to make a valid contribution about product customization decision and suggesting future studies from other perspectives.