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The purpose of this article is to explore the three types of water-based recreationists' (nonmotorized, motorized, and dual participants) perception on recreation conflict as well as their use of coping mechanisms and further understand the influence of specialization level on their choice of coping mechanism. Recreationists were divided into three groups based on the concept of experience use history. Data were collected between June and September 2007 at entry of five intra-site water recreation areas with every five individuals selected. Study findings partly supported the predictive relationships. Among all three groups (motorized, nonmotorized, and dual participants), less conflict was reported for nonmotorized participants than motored participants. Moreover, the data also suggest that coping mechanisms are widely employed in outdoor recreation. Implications for future research and practice were discussed.

This paper has two main aims: to show responses like yes or very likely for inbound visitors returning to a destination can lead to misleading and unreliable information; and to clarify the kind of information that should be collected.

Responses from Taiwan's inbound visitors relating to returning are examined to see what can be learned. Modeling is used to extract meaningful quantitative information from data.

Modeling shows that survey responses about return are inconsistent. Although 95 percent of non‐visiting‐friends‐and‐relations (VFR) leisure visitors indicate returning, this is not consistent with a retention rate of 90 percent. A retention rate of 33 percent is consistent with the observation that 70 percent of person‐visits are first‐visits. However, 33 percent retention is not consistent with over 95 percent of visitors returning. Conventional questions are yielding highly unreliable information and, therefore, data collection should be changed.

Relations between vague questions and return trips have been established. This research provides new evidence of the need for return data to include information allowing estimation of volume and timing of return.

The basic concept of transaction cost theory is that firms like to conduct transactions in a channel with lower transaction costs. Therefore, the purpose of this paper is to use the transaction cost perspective to identify which conditions cause companies to choose between outbound open innovation (hierarchy governance) and inbound open innovation (market governance).

Accordingly, transaction cost economics was used to relate the choice and implementation of open innovation using a sample of 250 electronics and information start-ups in China. Structural equation modeling was used to conduct confirmatory factor analysis to evaluate measurement model, while logistic regression analysis was used to test the hypotheses.

As expected, the dedicated asset specificity, human asset specificity, behavioral uncertainty, transaction frequency, and small number exchange were positively associated with outbound open innovation.

The contribution of this paper lies in explaining the role played by transaction cost economics in the process of open innovation for start-ups through empirical analysis.

A new optimization model for setting the target values of the technical attributes of a product is presented. The framework not only considers customer satisfaction targets, but also the cost target. This enables one to weigh the trade‐off between these two objectives according to his preferences. The formulation is capable of generating a set of Pareto‐optimal solutions with respect to customer satisfaction and cost thus allowing the development team to explore their viability in relation to the subsequent houses of quality. At the same time, the scheme is simple enough to be implemented using a spreadsheet and the Excel solver. Uses a desirability function approach to represent the technical attributes’ values so as to adapt to different directions of improvement for different technical attributes. For illustration purposes, a case study of a digital camera is presented using a simpler variant of the model so that various sensitivity analyses can be performed.

Assessing air cargo strategy from an airport's perspective is relatively novel, and it seems little attention has been paid to this research area. This chapter will address this research gap by introducing an Airport Cargo Strategy Canvas, designed to help build cargo strategies for individual airports.

The Airport Cargo Strategy Canvas can be used as a tool to analyze and improve the air cargo strategy of an airport. The first part of this chapter will explain the different components of the Airport Cargo Strategy Canvas more in detail. The horizontal axis on the canvas differentiates between exogenous and endogenous drivers of airport competitiveness. The vertical axis distinguishes between the airport product and the airport market. The canvas also considers potential disruptors and principal shareholders' objectives. The different components of the canvas allow the analyst to dig into the main features and differentiators of respective airports. The canvas might also be helpful to structure and compare the strategic components and framework of their own or competitors' cargo strategies.

In the second part, the Airport Cargo Strategy Canvas was applied to Brussels Airport to analyze its cargo strategy. The canvas showed several strengths and weaknesses, opportunities and threats in its current cargo strategy. The completed canvas will let Brussels Airport's executives explore and analyze the strategy of their main competitors and peers' strategy and help them identify potential gaps in their strategies.