Online search – Online purchase in franchising: An empirical analysis of franchisor website functionality

The aim of this paper is to characterize franchisors’ e-commerce strategies by studying their website functionality. Franchisors can use their website to facilitate consumer search. They can also provide content and tools to promote online purchasing (e.g., promotion codes, online payment, delivery options). Why are some franchisor websites more “search oriented”? What are the factors that influence the provision of informational tools and/or transactional tools? This empirical study is based on a detailed observation of 130 e-commerce websites of franchisors operating their chains in the French market.     

How collaborative routines improve dynamic innovation capability and performance in tourism industry? A path-dependent learning model

Current results of direct relationships between collaboration and innovation capability on performance in tourism contexts are inconsistent. This research is to uncover roles of collaborative routines on promoting relationships between internal and service innovation capabilities as two distinct mechanisms, and performance. The study also examines the contingent effect of knowledge search on performance. Survey data from 181 samples from the Thai tourism industry are gathered for analyses. Findings demonstrate that knowledge search and internal innovation capability have a direct impact on performance, whereas the effect of service innovation capability on performance is significant only in the presence of collaborative routines.     

EEC双通道健康度评估方法研究

为了解决航空发动机双通道电子控制器(EEC)两个通道均发生故障时如何评估通道健康度,从而选择主控通道的问题,论文提出了基于逆模型计算发动机推力敏感度的方法,量化不同信号故障对发动机推力的影响程度,依据推力敏感度来评估双通道健康度,协助主控通道选择,最终提高系统的安全性。     

控制柴油机冒烟的措施

在减轻大气污染对策的问题里,严格治理柴油机冒烟具有重要意义。     

Resilience of sustainability‐oriented and financially‐driven organizations

To answer key questions concerning how negative and positive financial performance gaps motivate organizations to build more resilient systems, we develop a conceptual process model to reveal the process by which financially and sustainability‐driven organizations can translate these negative and positive financial performance gaps into organizational resilience. We specify the different modes of search behaviors that these organizations pursue when encountering negative and positive financial performance gaps. We then expand on group engagement model to theorize that vicarious search is likely to encourage limiting behaviors, whereas internal search is likely to foster promotion behaviors. Finally, we explain how both promoting and limiting behaviors can be helpful in improving organizational resilience. In this way, we hope to advance research that connects and integrates relatively disparate realms and, more specifically, to contribute to the sustainability, resilience, and performance feedback literatures.     

More on Middlemen: Equilibrium Entry and Efficiency in Intermediated Markets

This paper generalizes Rubinstein and Wolinsky's (1987) model of middlemen (intermediation) by incorporating production and search costs, plus more general matching and bargaining. This allows us to study many new issues, including entry, efficiency, and dynamics. In the benchmark model, equilibrium exists uniquely and involves production and intermediation for some parameters but not others. Sometimes intermediation is essential: the market operates if and only if middlemen are active. If bargaining powers are set correctly equilibrium is efficient; if not there can be too much or too little economic activity. This is novel, compared to the original Rubinstein–Wolinsky model, where equilibrium is always efficient.     

Job Search and the Measurement of Unemployment in South Africa

We interrogate the distinction between searching and non‐searching unemployment in South Africa using data from the first national panel survey that tracks the individual. In particular, we test whether the non‐searching unemployed display a weaker commitment to the labour market than the searching unemployed, and we investigate what counts as search activity. We find that over the panel, the search status of the unemployed does not predict their subsequent employment status, a result that is robust also for subsamples that vary by age cohort, gender and location. Moreover, social networks are the most important job‐finding strategy of the employed. These findings challenge the exclusion of the non‐searching unemployed from the measure of “genuine” work seekers.     

Short-term forecasting of Japanese tourist inflow to South Korea using Google trends data

We utilize the Internet search data from Google Trends to provide short-term forecasts for the inflow of Japanese tourists to South Korea. We construct the Google variable in a systematic way by combining keywords to minimize mean squared or mean absolute forecasting errors. We augment the Google variable to the standard time-series forecasting models and compare their forecasting accuracies. We find that Google-augmented models perform much better than the standard time-series models in terms of short-term forecasting accuracy. In particular, Google models show better out-of-sample forecasting performance than in-sample forecasting.     

An adaptive large-neighborhood search heuristic for a multi-period vehicle routing problem

This problem involves optimizing product collection and redistribution from production locations to a set of processing plants over a planning horizon. This horizon consists of several days, and the collection-redistribution is performed on a repeating daily basis. A single routing plan must be prepared for the whole horizon, taking into account the seasonal variations in the supply. We model the problem using a sequence of periods, each corresponding to a season. We propose an adaptive large-neighborhood search with several specifically designed operators and features. The results show the excellent performance of the algorithm in terms of solution quality and computational efficiency.     

Arc routing problems to restore connectivity of a road network

After a disaster, restoring accessibility in the affected area is critical for response operations. We study two arc routing problems for clearing blocked roads. The first problem minimizes the time to reconnect the road network, while the second maximizes the total benefit gained by reconnecting network components within a time limit. For each problem, we develop a mixed integer programming formulation and two versions of a heuristic algorithm. We conduct computational experiments on Istanbul data and instances adapted from the literature. The heuristics achieve near-optimal or optimal solutions quickly in most of the tested instances.