Examining ecotourism intention: The role of tourists' traits and environmental concerns

The study offers new insights by examining the influence of personality traits (extraversion and neuroticism) on tourists' intentions to visit ecotourism sites using the lens of the theory of planned behavior. It also investigates whether environmental knowledge moderates the effect of extraversion, neuroticism, and environmental concern on tourists' ecotourism intentions. We applied structural equation modeling on 350 responses collected through the Amazon M-Turk platform. Results highlight that extroverts are more likely to express ecotourism intentions than neurotic tourists. However, it was also noted that neurotic tourists' intention to visit ecotourism sites could be influenced if their environmental concerns were emphasized. The study offers important new insights to managers, policy-makers, and practitioners about the roles of personality traits, environmental knowledge, and environmental concern vis-a-vis their relative significance in shaping tourists' decision-making and choices for ecotourism sites. As a result, managers/practitioners need to devise specific communication strategies to enhance awareness and a sense of responsibility among neurotic tourists

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase 1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age  6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score  652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc = 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N = 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in Asia and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

Error-Smoothing Exponentially Weighted Moving Average for Improving Critical Dimension Performance in Photolithography Process

The increasingly stringent tolerance of linewidths is a result of shrinking feature size of integrated circuits, and thus the manufacturing process in wafer fabrication should be accurately controlled to maintain process yields. Critical dimension (CD) is defined as the minimum width of a photoresist line or space printed on an exposure pattern by a stepper or scanner in photolithography. The CD is measured using metrology equipment and is compensated by modifying the corresponding equipment setup parameters. A feedback message is then sent to the next wafer for pre-adjustment and a feedforward message is sent to the previous wafer for post-adjustment. This study aimed to address a manufacturing intelligence framework to improve CD performance in a photolithography process. The input recipe is updated for the next run that is based on recently measured process data through the modified controller called as an error-smoothing exponentially weighted moving average (E-EWMA); both process and information flows are considered. A case study with a run-to-run process control is conducted to compensate the process variation to demonstrate the proposed framework. The results demonstrate that the proposed E-EWMA outperforms the conventional EWMA used in the company.

Performance of Channel Members under Emission-Sensitive Demand for Green Supply Chain Management: A Game Theory Approach

The skyrocketing growth of e-commerce and traditional retailing contributes to a large proportion of carbon emissions in any supply chain. Nevertheless, the literature related to carbon emission has focused on manufacturers and their potential for emission reduction. Therefore, it is imperative to understand the role of the retailing sector in reducing carbon emissions. Therefore, this study considers emission-sensitive demands which are faced by an r-store (brick and mortar retailer) and an e-store (online retailer) under different channel power structures. The competition between the channel members is modeled using game theory for the following channel structures, i.e., (i) r-store and e-store have commensurate channel power, (ii) r-store holds higher channel power, and (iii) e-store holds higher channel power. Equilibrium analysis was carried out to obtain the optimal pricing strategies and the r-store’s optimal profit and e-store. Further, the pricing strategies and resulting sales volumes were compared analytically and followed by a numerical validation. Three subcases were considered under numerical examples based on the parameter values with special reference to the base demand. It was found that competition between the r-store and the e-store having commensurate channel power will make them worse off. Therefore, the channel leadership is neither helping the r-store nor the e-store obtain more profit when the customer demand is emission sensitive

An Integrated Model of Scenario Planning and Decision Tree Analysis for New Product Development Financial Planning: A Case of Smart Phone Development Project in Taiwan

Demands of smart phones have been rapidly and dramatically increasing whereas R&D and marketing of smart phones have been facing severer competition and more dynamic environment. Most existing studies of new product development (NPD) focused on the traditional net-present-value (NPV) method and the real option analysis which are lack of flexibility to model asymmetric multi-stage decisions and flexible uncertain states. This study aims to integrate scenario planning and decision tree analysis for NPD evaluation. In so doing, scenarios for modeling uncertainties can be generated systematically. A case study of a Taiwanese OEM company shows the viability of the proposed model. Compared with the performance of the realized decisions, the proposed analysis is more robust and lowering the risk to minimal with appropriate R&D resource allocation. A two-way sensitivity analysis helps determine boundaries of the probability of R&D success and the cost of R&D where the R&D project will become profitable

Effects of carbon-emission and setup cost reduction in a sustainable electrical energy supply chain inventory system

This article develops a sustainable electricity supply chain mathematical model that assumes linear price-dependent customer demands where the price is a decision variable under setup cost and carbon emission. The sustainable electrical supply chain system contained: (a) power generation; (b) transmission substations; (c) distribution substations; and (d) customer. The production rates depend on the demand rate, and demand for electricity by the customers is dependent on the price of electricity where the electrical energy was generated and transmitted through multiple substations to customers. Moreover, we considered that the capacities of transmission rates, power generation, and distances in between two stations are associated with the distribution costs and transmission cost. Here, we used the theory of inventory to develop a new model and suggested a procedure to deduce an optimal solution for this model. Finally, a numerical example and sensitivity analysis are employed to illustrate the present study and with managerial insights. © 2019 by the author

Process discovery by synthesizing activity proximity and user's domain knowledge

Process mining techniques assist users to automatically infer process models from event logs. However, the result of process model driven by traditional process mining technique may conflict with the knowledge of users due to some real conditions, i.e. alternative activity is selected due to equipment breakdown. First, the use of heuristics may detect inconsistencies caused by bad guess. Second, extraction of all possible ordering of events reflects historical observation that sometimes hinders users to obtain an ideal process model since the activity has some event types. Yet, the current process mining approach is not totally compatible with some aspects such as extra logs behavior and soundness of process model when the process model changes according to user requirements. This paper presents a method for synthesizing activity proximity from event logs in the area of process mining. The method derives a bounded graph that covers the extra-behavior of an event log according to user???s domain knowledge. Another important property is that it produces a graph with considering the proximity among activities that still contains the original behavior of the event log based on event types. The methods described in this paper have been implemented in ProM framework and tested on a set of real process examples. ?? Springer International Publishing Switzerland 2013

Optimizing a Sustainable Supply Chain Inventory Model for Controllable Deterioration and Emission Rates in a Greenhouse Farm

This study investigated how greenhouse managers should invest in preservation and green technologies and introduce trade credit to increase their profits. We propose a supply chain inventory model with controllable deterioration and emission rates under payment schemes for shortage and surplus, where demand depends on price and trade credit. Carbon emissions and deterioration are factors affecting global warming, and many greenhouse managers have focused on reducing carbon emissions. Carbon caps and tax-based incentives have been used in many greenhouses to achieve such reduction. Because of the importance of reducing carbon emissions for developing a green supply chain, various studies have investigated how firms deal with carbon emission constraints. In this continuation, we have used green technology to curb the excessive emissions from the environment or make it clean from CO2. In a seller–buyer relationship, the seller can offer a trade credit period to the buyer to manage stock and stimulate demand. Deterioration may become a challenge for most firms as they are under time constraints control, and preservation technology could help. This study proposes three novel inventory strategies for a sustainable supply chain (full backorder, partial backorder, and no backorder), linking all these important issues. The solution optimizes total annual profit for inventory shortage or surplus. We conducted a numerical study with three examples to evaluate the model’s authenticity and effectiveness and demonstrate the solution technique. The deterioration and emission rates can be included in a trade credit policy to increase greenhouse profits. The results suggest that greenhouse managers could apply the proposed model to manage real-world situations