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This article describes how mobile operators occasionally fail to provide adequate service quality due to network overload, blackouts, or coverage white spots. Customers can increase the quality of connections by multihoming, i.e. using subscriptions of several operators. Multihoming is facilitated by an innovative reprogrammable embedded SIM (eSIM) that can enable dynamic switching between networks. Although eSIM multihoming is advantageous, its future is not definite, as it is affected by multiple factors and actors with conflicting business interests. This paper defines scenarios for the evolution of eSIM multihoming and its possible impact on competition by constructing qualitative system dynamics models based on expert interviews. The results show that depending on market conditions and actions of stakeholders, multihoming may reach high diffusion, find application in special use cases, or fail to take off. With high diffusion, competition between operators will become more dynamic, and market share will be defined by the number of served sessions.

This article provides empirical evidence on the price and unit sales volume patterns of mobile handsets and mobile technologies, using data on the Finnish market. The prices and sales are studied on product category, product model, and product feature levels. The results show how the dynamic of prices and sales changed after the proliferation of smartphones. Otherwise, the dynamics seem to be relatively systematic supporting the use of simple assumptions in practical estimations. The median price of handset models decreases linearly, from 89% of the introduction price at peak sales in the fifth sales month to 47% in in two years. For mobile handset features, a decreasing price pattern was also identified. After a 10% market share is reached, the decrease is on average 30 Euros per 10% market share change. The prices at feature takeoff were identified to be on average at 58% of introduction price.

PurposeThis study aims to investigate the extent to which psychological factors and the agency of decision-makers drive outsourcing decisions. Arguments based on transaction cost economics, the core competence approach and the theory of planned behavior are used to explain logistics outsourcing.Design/methodology/approachThe literature was reviewed to identify constructs that are antecedents of logistics outsourcing intentions, and corresponding measures were developed. The data were gathered through a survey of supply chain professionals in Finnish manufacturing companies. A measurement model was reviewed to ensure reliability and validity and converted into a structural model for analysis. The analysis was based on partial least squares (PLS) structural equation modeling.FindingsSupply chain managers objectively consider the characteristics of their organization's logistics identified in previous research as requiring assessment during the outsourcing process. However, and surprisingly, they also tend to rely on behavioral subjective factors such as positive attitudes, encouraging subjective norms and competence. Moreover, it seems that firms do not outsource logistics activities despite the high strategic importance of the function, but because of it.Research limitations/implicationsThe constructed model is limited to the constructs chosen to represent drivers of logistics outsourcing. Further application with more samples would improve its reliability.Practical implicationsThe factors proposed here with respect to assets and the capabilities of third-party partners could facilitate decision-making related to logistics outsourcing.Originality/valueThe findings emphasize the role of behavioral factors in the procurement function and therefore enhance the understanding of behavioral supply chain management.

PurposeThe size of the logistics market is typically estimated from the national accounting and market data. However, this data does not take certain in-house logistics services into account and most likely underestimates the true size of the market. The purpose of this paper is to develop a method for estimating the potential size of the logistics market in terms of overall logistics expenditure and to also account for in-house services.Design/methodology/approachThe research approach involves combining longitudinal industry- and firm-level turnover data, incorporating survey data from Finland on logistics outsourcing and costs, and calculating yearly logistics expenditure and the market demand for logistics services. Descriptive statistics, weighted arithmetic means and analyses of variance are employed in the estimations.FindingsThe research suggests and demonstrates a rigorous method for estimating the size of the logistics market, including both market-based demand and in-house services.Research limitations/implicationsThe empirical data used to illustrate the result are limited to a single country. The methodology should be further validated with data from other countries. The quality of the survey data could be improved by targeting multiple informants from a single firm.Social implicationsOne outcome of the research is that policymakers will be better able to estimate the size of the logistics market on a national level. For service providers, the results provide additional information on the market potential of logistics services.Originality/valueThe novelty of the research lies in combining multiple data sources and expanding the estimation of the logistics market to include services provided in-house.

PurposeTo explore the present logistics performance of Finnish small and medium‐sized enterprises (SMEs) and to analyse the relationship between logistics performance and financial performance in these firms.Design/methodology/approachThe dataset comprises 424 SMEs that participated in a nationwide Finnish logistics survey in 2006. Logistics performance measures were derived from the survey data, and based on these values logistically top‐performing firms were identified within different industry groups. The financial performance of these firms was then examined vis‐à‐vis their industry peers using financial reports‐based data.FindingsThe results imply that the overall level of logistics performance among the examined companies might be at such an elementary level that no statistically observable positive linkage between logistics performance and financial performance exists. The group of firms for whom logistics is a key source of competitive advantage in this sample is small and therefore statistical analysis at an industry level might be too aggregate to reveal this linkage. It is also surprising that service level and logistics cost efficiency are positively related; thus, companies who have a relatively high‐service level tend to have relative low‐logistics costs. These findings might imply that logistics is just starting to gain more attention among SMEs in Finland and at least in the short‐term, it might be relatively easy for SMEs to gain competitive advantage by focusing more on logistics performance.Originality/valueThis study is the first large‐scale attempt to focus on the logistics performance of SMEs and analyse the linkages between financial and logistics performance among the companies using both self‐reported data and financial reports‐based data. In addition, a theoretical framework of the linkages between logistics performance and financial performance is suggested and revised based on the findings of the study. The revised framework requires testing as a part of future research.