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.     

Web users’ behavioural patterns of tourism information search: From online to offline

This paper presents a conceptual framework of Web users’ engagement in tourism information search for a comprehensive understanding of their integrated online and offline search behaviour. The information search experiences are characterised as a process constituting some common elements: prior knowledge and searching experiences, online searching strategies, processing and recording information, barriers to online searching, reasons for ending an online search, summarising information, exchanging information and searching for more information through other sources. Such behaviour goes beyond the scope of information searching and captures the other activities, including information processing, utilising and disseminating. The grounded theory research method is employed as an inductive investigative process in which the authors construct the framework by systematically collecting and analysing data. The aim of this research method is to build a theory. The data sets consist of both semi-structured in-depth interviews with subjects and their field observations based on online searching. A theoretical model incorporating 10 propositions is proposed for future testing.     

The effect of shopping goals and in-store mobile device use on purchase outcomes in brick-and-mortar stores

The present study examines the effect of using a mobile device on search and evaluation by a shopper in a brick-and-mortar store. A conceptual model that proposes inter-relationships between shopping goals, the amount and type of in-store mobile device use, and purchase outcomes is developed. Data from a national quota sample of 1034 mobile shoppers is used to test hypotheses derived from the proposed model. The findings provide several new insights into the impact of in-store mobile device use on the consumer decision journey in a brick-and-mortar store. Depending upon the shopping goals of the consumer, the use of a mobile device by shoppers in a brick-and-mortar store can either decrease or increase search, lead to more deferred purchases or in-store-now purchases, and more online or physical store purchases. The study is among the first to model the pathway to purchase for mobile device assisted shoppers in brick-and-mortar stores.     

Search reduction in hierarchical distributed problem solving

Knoblock and Korf have determined that abstraction can reduce search at a single agent from exponential to linear complexity (Knoblock 1991; Korf 1987). We extend their results by showing how concurrent problem solving among multiple agents using abstraction can further reduce search to logarithmic complexity. We empirically validate our formal analysis by showing that it correctly predicts performance for the Towers of Hanoi problem (which meets all of the assumptions of the analysis). Furthermore, a powerful form of abstraction for large multiagent systems is to group agents into teams, and teams of agents into larger teams, to form an organizational pyramid. We apply our analysis to such an organization of agents and demonstrate the results in a delivery task domain. Our predictions about abstraction's benefits can also be met in this more realistic domain, even though assumptions made in our analysis are violated. Our analytical results thus hold the promise for explaining in general terms many experimental observations made in specific distributed AI systems, and we demonstrate this ability with examples from prior research.This research has been sponsored, in part, by the National Science Foundation under grants IRI-9015423 and IRI-9010645, by the University of Michigan Rackham Graduate School, and by a Bell Northern Research Postgraduate Award.     

基于信息检索与搜索引擎数据挖掘方法探究

本文主要分析了信息检索与搜索引擎相关问题,首先给出了信息检索的基本原理,重点探讨了信息检索与信息存储的之间的关系问题,同时给出了信息检索的效率以及检索系统的评价体系,分析了人工检索和计算机检索的不同与联系。