A complex decision-making challenge senior managers commonly face is the selection of the winning bid from multiple project proposals. Project selection decisions become more complex when providers deliberately choose to introduce ambiguity to their project proposals rather than address the client's predetermined set of desired specifications. In particular, providers suggest in their proposals a range

Online social networks convey rich information about geospatial facets of reality. However in most cases, geographic information is not explicit and structured, thus preventing its exploitation in real-time applications. We address this limitation by introducing a novel geoparsing and geotagging technique called Geo-Semantic-Parsing (GSP). GSP identifies location references in free text and extracts

With the goal of devising algorithms for decision support in operational tasks, we introduce a new methodology for the automated configuration of algorithms for combinatorial online optimization problems. The procedure draws upon available instance data and is capable of recognizing data patterns which prove beneficial to the overall outcome. Since online optimization requires repetitive decision making

The increased exposure of the average citizen and customer to polarised content from various sources has been of significant consequence for companies and governmental organisations. Such content has, for example, served as a catalyst for violent uprisings and shifts in stock market prices. The collection and study of opinion have therefore become a necessity in many industries. Due to the vast nature

Many real-world networks have signed relationships between the nodes. Identification of these relationships is an important aspect of decision making. The existing signed relationships in a network may impact the relationships between the other nodes, hence learning from the existing signed relationships in a network can be used for decision making in various mining tasks. These signed networks are

In recent years, new types of interactive analytical dashboard features have emerged for operational decision support systems (DSS). Analytical components of such features solve optimization problems hidden from the human eye, whereas interactive components involve the individual in the optimization process via graphical user interfaces (GUIs). Despite their expected value for organizations, little

Along with recent advancement of web technologies, social networking sites (SNSs) affect peoples lifestyles by enabling them to perform so many activities which were not easy to do before. However, protection of users' disclosed information becomes an important challenge not only for SNS users but also for governing organizations. This study focuses on SNS users' protection from privacy breaches that

Online learning has been adopted rapidly by educational institutions and organizations. Despite its many advantages, including 24/7 access, high flexibility, rich content, and low cost, online learning suffers from high dropout rates that hamper pedagogical and economic goal outcomes. Enhanced student dropout prediction tools would help providers proactively detect students at risk of leaving and identify

Reward-based crowdfunding provides a unique instrument to acquire capital from small investors for a specific project. To successfully campaign for the desired funds, however, entrepreneurs also need to understand the subconscious factors, which influence the funding behavior of potential investors. In pursuit of that goal, this study examines how facial emotional expressions, which are shown in the

Despite a consensus that sales of physical albums have declined with the increasing prevalence of digital music, this seemingly unequivocal observation may not be true. Physical formats still occupy a fraction of the market, with a noticeable increase in the sales of physical albums in a few countries where digital media is predominant. This study empirically examines the impact of two online music

When an aircraft experiences an unexpected issue during flight operations, a technician determines whether the aircraft can safely perform the next flight. This operational decision process - known as dispatch assessment - has to happen within limited available time between aircraft arrival and departure. Currently, technicians face two main problems during the assessment: lack of access to decision

The recent COVID-19 pandemic has clearly shown how agricultural foods and e-commerce initiatives are critical for many organizations, regions, and countries worldwide. Despite this vital importance, prior IS research on the business value of IT has not paid enough attention to the potential specificities of the agribusinesses. This study examines the impact of e-commerce capability on business agility

In recent decades, the implementation of electronic health record (EHR) systems has been evolving worldwide, leading to the creation of immense data volume in healthcare. Moreover, there has been a call for research studies to enhance personalized medicine and develop clinical decision support systems (CDSS) by analyzing the available EHR data. In EHR data, usually, there are millions of patients records

This paper considers a multi-item newsvendor problem with a capacity constraint (Z). The problem has already been addressed in the literature using the classical newsvendor problem. However, provided solutions made assumptions for demand distributions, which are often incorrect and led to errors in the inventory optimization. This research proposes a distribution-free and completely data-driven solution

The criteria for evaluating a crowdfunding project vary from person to person. Some investors are concerned with the entrepreneurs' profiles, while others are more interested in the creativity behind the project. Most investors evaluate a project by referring to founder-generated content. Entrepreneurs face the choice of emphasizing their own profiles or the project creativity within the limited narrative

Hinterland intermodal transportation is the movement of containers between deep-sea ports and inland terminals by using trucks, trains, barges, or any combination of them. Synchromodal transportation, as an extension of intermodal transportation, refers to transport systems with dynamic updating of plans by incorporating real-time information. The trend towards spot markets and digitalization in hinterland

Uplift modeling is an approach for estimating the incremental effect of an action or treatment at the individual level. It has gained attention in the marketing and analytics communities due to its ability to adequately model the effect of direct marketing actions via predictive analytics. The main contribution of our study is the implementation of the uplift modeling framework to maximize the effectiveness

Deterioration rate is an important characteristic of perishable products. While deterioration in perishables is unavoidable, there are proven ways to lower their deterioration rates. Deterioration rate is commonly treated as an exogenous parameter in extant inventory management literature. We define deterioration rate as one of the controllable variables and propose a novel freshness-preservation effort

Shared parking firms offer a double-sided platform for parking space sharing. Many of these firms provide differentiated service levels to both suppliers and buyers. This new phenomenon in the parking industry materialized thanks to recent innovations in IoT-enabled automation and electric vehicle charging technologies. We study shared parking firms. Specifically, we formulate the firm's location and

In consideration of the general lack of trust in human professional financial advisors due to conflicts of interest, and given inadequacies in terms of the utility of FinTech alternatives for financial goal recommendations, this study establishes a framework for an ontology-based, multiagent recommender system designed to improve financial capability through the recommendation of financial goals, called

Imagine that you are a marketer with a good product but mediocre online reviews. When would be the best time to present the review score information to consumers: before the product description, with the product description, or after the product description? In order to answer this question, we carried out three online experiments in which we manipulated the order of information (reviews presented

In light of individuals' increasing concern regarding their physical health, mobile health applications (mHealth Apps) have gained popularity in recent years as important tools for addressing health problems. However, users find it challenging to choose appropriate mHealth Apps, as these Apps incorporate diverse behavior change techniques (BCTs), and their individual behavioral intervention effects

Process mining, as with any form of data analysis, relies heavily on the quality of input data to generate accurate and reliable results. A fit-for-purpose event log nearly always requires time-consuming, manual pre-processing to extract events from source data, with data quality dependent on the analyst's domain knowledge and skills. Despite much being written about data quality in general, a generalisable

Accurate prediction of no-show patients plays a crucial role as it enables researchers to increase the efficiency of their scheduling systems. The purpose of the current study is to formulate a novel hybrid data mining-based methodology to a) accurately predict the no-show patients, b) build a parsimonious model by employing a comprehensive variable selection procedure, c) build a model that does not

We develop a secure attribute-based search protocol for Radio Frequency Identification (RFID) systems. This protocol can be used to simultaneously identify groups of items that share a set of attribute values. To the best of our knowledge, this is the first such work with the potential to significantly enhance the security and intelligence of RFID-enabled applications in inventory control and supply

Clinician guidelines recommend health management to tailor the form of care to the expected course of diseases. Hence, in order to decide upon a suitable treatment plan, health professionals benefit from decision support, i.e., predictions about how a disease is to evolve. In clinical practice, such a prediction model requires interpretability. Interpretability, however, is often precluded by complex

Fake online reviews in e-commerce significantly affect online consumers, merchants, and, as a result, market efficiency. Despite scholarly efforts to examine fake reviews, there still lacks a survey that can systematically analyze and summarize its antecedents and consequences. This study proposes an antecedent–consequence–intervention conceptual framework to develop an initial research agenda for

The review systems of online platforms create a stream of online word-of-mouth that allows consumers to learn from others' purchasing experience. However, it is difficult for consumers to discern the authenticity of a review or the reviewer's level of experience with the product. Platforms can aid the authentication process by incorporating a verified purchase (VP) indication, or “badge” as is done

Humankind faces many “wicked” decision-making problems, which must be solved. One promising approach refers to crowdsourcing systems that hold the potential to solve any kind of problem – notably wicked ones. Crowdsourced solutions work well because crowds exchange knowledge from different domains – a concept known as “cross-fertilisation.” Thereby, the “facilitator” of a crowdsourcing system is the

A central concern for the long-term vibrancy of virtual communities is how to effectively motivate continuous contributions from community members. To address this challenge, a series of motivation factors that range from self-interest driven to prosocial-oriented motives have been identified by scholars. As members participate in continuous contributions and community activities alike, their status

Evidence suggests that firms which use customer data analytics perform better than those that do not. However, the current policy of voluntary profiling allows firms to collect and use customer information only if customers voluntarily disclose information with them. Further, surveys and literature show that many customers are not comfortable with firms collecting their information due to privacy concerns

This paper introduces the concept of IT wisdom from a perspective of meta-capability and establishes the relationship between IT wisdom and firm performance. We propose that IT wisdom as a holistic meta-IT capability of a firm can strategically enable and exercise suitable IT capabilities and organizational capabilities to adapt to changing environments for improving firm performance. We test our hypotheses

“Showrooming”, a practice where consumers visit a brick-and-mortar store to examine and research a product before buying it online, is being increasingly observed in recent times. This not only adversely affects the physical store but also the manufacturer in the long run. Showrooming leads to reduced sales efforts on the part of the brick-and-mortar retailer which leads to a decline in showcasing

Graph-based anomaly detection (GBAD) approaches are among the most popular techniques used to analyze connectivity patterns in communication networks and identify suspicious behaviors. Given the different GBAD approaches proposed for fraud detection, in this study, we develop a framework to synthesize the existing literature on the application of GBAD methods in fraud detection published between 2007

Proliferating applications of deep learning, along with the prevalence of large-scale text datasets, have revolutionized the natural language processing (NLP) field, thereby driving the recent explosive growth. Nevertheless, it is argued that state-of-the-art studies focus excessively on producing quantitative performances superior to existing models, by playing “the Kaggle game.” Hence, the field

In this paper, we propose a comprehensive analytics framework that can serve as a decision support tool for HR recruiters in real-world settings in order to improve hiring and placement decisions. The proposed framework follows two main phases: a local prediction scheme for recruitments' success at the level of a single job placement, and a mathematical model that provides a global recruitment optimization

Business process simulation is a versatile technique to estimate the performance of a process under multiple scenarios. This, in turn, allows analysts to compare alternative options to improve a business process. A common roadblock for business process simulation is that constructing accurate simulation models is cumbersome and error-prone. Modern information systems store detailed execution logs of

Trust plays an important role in sharing transactions on short-term rental platforms. However, the impact of host self-description on trust perception and whether trust perception can influence purchase behavior remain under-studied. Therefore, a text analytics framework was proposed to research the relationships among host self-description, trust perception and purchase behavior on Airbnb. Specifically

Today, customers can conveniently compare products and decide how to interact with companies. With customer centricity becoming an important success factor, companies must drive customer satisfaction not only through excellent products but also through customer-centric processes. As many companies face an abundance of action possibilities, fast-changing customer needs, and scarce resources, guidance

This paper examines online users' perceived susceptibility to phishing attacks. We posit that an individual's phishing susceptibility may be shaped by recent phishing encounters and, more importantly, that the effect of new experience on susceptibility will be heterogeneous among users. To facilitate our investigation, we focus on both the process and outcome of phishing detection. Survey data from

This paper studies a reward-based crowdfunding game wherein the creator first collects money through an E-crowdfunding platform and then, if successful, invests the raised money to fund promotional activities via online retailing. We derive the creator's equilibrium decisions and the corresponding payoff and show that they are significantly influenced by the potential demand and the gap between different

Effectively displaying goods in search results is valuable for B2C merchants to earn clicks from consumers and even increase sales. Taking down jackets and trousers sold on Tmall—China's largest B2C e-commerce platform—as the example, this paper collects data about three factors that influence consumers' first impression on their search results: the price of a product, the quantity of historical reviews

Safety, as the most important concern in civil aviation, needs to be maintained at an acceptable level at all times in the air transportation system. This paper aims to increase en-route flight safety through the development of deep learning models for trajectory prediction, where model prediction uncertainty is characterized following a Bayesian approach. The proposed methodology consists of four

Online auctions use a variety of unique tools to provide quality signals for products and sellers in an attempt to overcome the online marketplace's limitations. These tools include feedback ratings and symbols that indicate reputation. However, surprisingly few studies have investigated the effects of reputation indicators in the decision-making process in online marketplaces. No prior study in our

Companies are increasingly conscious of the importance of Enterprise Architecture (EA) to represent and manage IT and business in a holistic way. EA modelling has become decisive to achieve models that accurately represents behaviour and assets of companies and lead them to make appropriate business decisions. Although EA representations can be manually modelled by experts, automatic EA modelling methods

Digital Assistants (DA) such as Amazon Alexa, Siri, or Google Assistant are now gaining great diffusion, since they allow users to execute a wide range of actions through messages in natural language. Even though DAs are able to complete tasks such as sending texts, making phone calls, or playing songs, they do not yet implement recommendation facilities. In this paper, we investigate the combination

We investigate the impacts of the decision support system's recommendations on decision makers' psychology and decision behaviors under uncertain contexts where optimal solutions exist. As a representative of such contexts, the newsvendor problem is studied by using the method of laboratory experiments. Through providing an elaborately designed decision support system in Experiment I, we validate that

The advent of new media, such as Google, Twitter, and Facebook, has offered the movie industry new opportunities to market movies and increase sales. In this study, we investigate the relationship between online media activities and movie sales. In particular, this paper examines how media coverage (online news and social media posts) and consumer engagement (information search and reading) affect

This paper proposes a decision support tool for maintenance capacity planning of complex product systems. The tool – ForeSim-BI – addresses the problem faced by maintenance organizations in forecasting the workload of future maintenance interventions and in planning an adequate capacity to face that expected workload. Developed and implemented from a predictive analytics perspective in the particular

Given the increasing competition to attract new customers, e-commerce providers (i.e., e-tailers) are being urged to optimize their website onboarding journeys. Design mechanisms employing social influence tactics seem to be promising avenues to effectively improve user onboarding experiences. Specifically, two social influence tactics—namely, reciprocity and social proof—are widely used in practice

This paper studies, designs and implements a new type of emergency decision support system that aims to improve the decision-making of emergency managers in crisis situations by connecting them to new, multiple data sources. The system combines event-driven and model-driven architectures and is dedicated to crisis cells. After its implementation, the system is evaluated using a realistic crisis scenario

Toy-related injuries account for a significant number of childhood injuries and the prevention of these injuries remains a goal for regulatory agencies and manufacturers. Text-mining is an increasingly prevalent method for uncovering the significance of words using big data. This research sets out to determine the effectiveness of text-mining in uncovering potentially dangerous children's toys. We

The prevalence of social media has greatly catalyzed the dissemination and proliferation of online memes (e.g., ideas, topics, melodies, tags, etc.). However, this information abundance is exceeding the capability of online users to consume it. Ranking memes based on their popularities could promote online advertisement and content distribution. Despite such importance, few existing work can solve

Technologies for automated detection of neonatal seizures are gradually moving towards cot-side implementation. The aim of this paper is to present different ways to visualize the output of a neonatal seizure detection system and analyse their influence on performance in a clinical environment. Three different ways to visualize the detector output are considered: a binary output, a probabilistic trace

Organizations today regularly share their customer data with their partners to gain competitive advantages. They are also often requested or even required by a third party to provide customer data that are deemed sensitive. In these circumstances, organizations are obligated to protect the privacy of the individuals involved while still benefiting from sharing data or meeting the requirement for releasing

Over time, data warehouse (DW) systems have become more difficult to develop because of the growing heterogeneity of data sources. Despite advances in research and technology, DW projects are still too slow for pragmatic results to be generated. Here, we address the following question: how can the complexity of DW development for integration of heterogeneous transactional information systems be reduced

The way information is presented influences human decision making and is consequently highly relevant to electronically supported negotiations. The present study analyzes in a controlled laboratory experiment how information presentation in three alternative formats (table, history graph and dance graph) influences the negotiators' behavior and negotiation outcomes. The results show that graphical

Discrete multi-criteria decision problems with numerous Pareto-efficient solution candidates place a significant cognitive burden on the decision maker. An interactive, aspiration-based search process that iteratively progresses toward the most preferred solution can alleviate this task. In this paper, we study three ways of representing such problems in a DSS, and compare them in a laboratory experiment