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The purpose of this paper, on innovative design of traditional weft-backed woven fabric, is to investigate a design principle and method for full-backed structure with double-faced shading effect to realize two types of double-faced shading effects for traditional weft-backed fabric that are impossible to be realized under plane design mode. In addition, the study on the color rendering law is conducive to the design application, and the effectiveness of the design method has been verified by the design practices.

This paper presents a design method for full-backed structure with two shaded weave databases (SWDs) by selecting two primary weaves (PWs), establishing the corresponding SWDs, selecting the proper compound structures for database of full-backed structure with double-faced shading effect. Color card fabric with 544 specimens is produced and their color values are measured, their color difference and variance are analyzed to evaluate the color rendering characteristics. Finally, double-faced weft-backed fabrics are produced under layered-combination design mode to verify the practicality of full-backed structure with double-faced shading effect.

Weft-backed woven fabrics with “SPDC” (same pattern and different color) and “DPDC” (different pattern and different color) shading effects can be produced using full-backed structure with double-faced shading effect. The color expression is extremely enhanced (136 compound structures on one side for one color weft). In the shading process, two sets of wefts do not affect each other, and stable and ideal color shading effect with high color purity can be expressed according to the analyses on the L* (lightness) values, color purity, color differences (0.47–3.20) and variance (0.25–1.21) of the color card fabric.

Breaking through the structural limitations and achieving the double-faced shading effects that cannot be expressed in plane design mode. The research on two weft-backed fabric with the most basic weft-backed structure provides not only a theoretical base for further study on weft-backed structures, but also some references for structure innovation design of traditional weft-backed woven fabrics.

Research has shown that more than half of attempted recovery efforts only reinforce dissatisfaction, producing a “double deviation” effect. Surprisingly, these double deviation effects have received little attention in service marketing literature. To fill this gap, this paper aims to develop and empirically test a model of how customers form satisfaction judgments in double deviation scenarios. The paper seeks to propose that emotions have a distinct and separate influence from perceived justice in explaining satisfaction with failed recovery.

The paper employs the critical incident technique to obtain data from banking customers and apply latent variable path analysis to test the proposed model.

The results of the study support the model and highlight the important role of specific recovery‐related emotions in double deviation contexts.

Future research should try to determine whether different specific negative emotions and/or the interactional and procedural components of justice affect post‐recovery judgments in double deviation scenarios.

The results show that specific emotions such as anger play an important role in explaining satisfaction with service recovery. The paper proposes that in future, customer satisfaction surveys could include items measuring specific emotions. This could increase their efficiency as managerial tools.

To the authors' knowledge, this has been the first attempt to model the effect of specific emotions triggered by the service recovery on satisfaction with service recovery and to empirically test a model of satisfaction with service recovery in double deviation scenarios. Furthermore, this study is based on the analysis of real service failures and recovery strategies.

The satisfaction and loyalty research argues that customer satisfaction is an antecedent to share of wallet (SOW). The double jeopardy view, however, argues that satisfaction and SOW levels are driven exclusively by penetration levels. Customer satisfaction and penetration, however, are not always positively related. The purpose of this paper is to explore the relevance and validity of these two divergent perspectives to creating growth in customer share of spending.

The authors examine a series of models evaluating the impact of both the relative penetration of a brand, and the satisfaction ratings of its customers on SOW using data covering 11 industry sectors, 188 brands, and 4,263 customers.

The authors find that part of the problem in reconciling these two views has been in how satisfaction is measured and analyzed. When using absolute satisfaction ratings of the firm/brand, the explanatory power of satisfaction on SOW is very weak at both the individual and firm level. When using satisfaction metrics relative to other competing brands, however, satisfaction is a strong predictor of customers’ share of category spending.

As predicted by double jeopardy, penetration is a strong predictor of firm-level SOW, but has almost no explanatory power at the individual level.

Managers need to focus on both improving penetration/reach and becoming the preferred brand in a customer’s usage set.

The research examines if (and if yes, how) satisfaction and penetration contribute to customers’ SOW allocations both at the individual and brand level.

The theory of double jeopardy (DJ) is shown to hold across broad ranging geographies and physical product categories. However, there is very little research appertaining to the subject within an online environment. In particular, studies that investigate the presence of DJ and the contrasting view point to DJ, namely, that of negative double jeopardy (NDJ), are lacking. This study aims to contribute to this identified research gap and examines the presence of DJ and NDJ within a product category, utilising data from Twitter.

A total of 354,676 tweets are scraped from Twitter and their sentiment analysed and allocated into positive, negative and no-opinion clusters using fuzzy c-means clustering. The sentiment is then compared to the market share of brands within the beer product category to establish whether a DJ or NDJ effect is present.

Data reveal an NDJ effect with regards to original tweets (i.e. tweets which have not been retweeted). That is, when analysing tweets relating to brands within a defined beer category, the authors find that larger brands suffer by having an increased negativity amongst the larger proportion of tweets associated with them.

The clustering approach to analyse sentiment in Twitter data brings a new direction to analysis of such sentiment. Future consideration of different numbers of clusters may further the insights this form of analysis can bring to the DJ/NDJ phenomenon. Managerial implications discuss the uncovered practitioner’s paradox of NDJ and strategies for dealing with DJ and NDJ effects.

This study is the first to explore the presence of DJ and NDJ through the utilisation of sentiment analysis-derived data and fuzzy clustering. DJ and NDJ are under-explored constructs in the online environment. Typically, past research examines DJ and NDJ in separate and detached fashions. Thus, the study is of theoretical value because it outlines boundaries to the DJ and NDJ conditions. Second, this research is the first study to analyse the sentiment of consumer-authored tweets to explore DJ and NDJ effects. Finally, the current study offers valuable insight into the DJ and NDJ effects for practicing marketing managers.

In daily marketing practices, when launching and promoting new products, marketers often induce consumers’ awe of nature via exposing consumers to beautiful natural scenes. Does this marketing practice really facilitate consumers’ subsequent new product choice? Existing awe research and new product research have not examined this issue yet. The purpose of this study is to study whether the marketing practice of awe induction faciliates consumers' new product choice.

This paper examines the double-edged sword effect of different types of awe on consumers’ adoption of new products. The authors conducted five experiments using various product categories (soft drinks, juices, cookies and watches), various many sources of sample types (college student samples and adult samples) and various manipulation of awe. The authors also focused on both new products with incongruent visual appearance (Experiment 1a, Experiment 1c, Experiment 2 and Experiment 3) and new products with incongruent conceptual attributes (Experiment 1b) to enhance the rigor of the experiments and the generalizability of the conclusions.

The authors find that when consumers perceive awe of threatening natural phenomena, they decrease their choice of moderately incongruent new products (positive effect), while when consumers perceive awe of beautiful natural phenomena, they increase their choice of moderately incongruent new products (negative effect). Also, this paper finds that the emergence of the positive of the double-edged sword effect is driven by the sequential mediation of the need for accommodation and openness to new experiences, while the emergence of the negative of the double-edged sword effect is driven by the uncertainty reduction motive.

This research has important theoretical implications. First, this paper advances existing awe research by reconciling the inconsistent findings in existing awe research by categorizing awe of nature. Second, this paper advances existing research on new products and moderate incongruity effects by exploring when the moderate incongruity effect exists and when it reverses in the new products field through the classification of awe of nature.

This study has rich implications for marketing management. First, marketers can facilitate consumers’ adoption of moderate incongruent new product via priming consumers’ awe of beautiful nature. Second, this paper suggests that marketers and brand managers should carefully choose the timing of new product launches to avoid inducing consumer awe of threatening nature (e.g. immediately after a severe natural disaster). Finally, the results of Experiment 3 in this paper suggest that when marketers want to launch new products with moderate incongruity, they need to target consumers with high cognitive flexibility.

This paper discusses how different types of awe affect consumers’ attitudes and choice of moderately new products. This research question has its social value in helping marketers, companies, consumers and society know the power of awe of nature on the behaviors and decision-making.

To the best of the author’s knowledge, this paper is among the first ones to examine the double-edged sword effect of different types of awe of nature on consumers’ new product adoption.

A visual sweetness scale with an arrow pointing to a specific sweetness level is now required on all labels of AOC Alsace. The sweetness scale makes it easier for consumers to understand what is in the bottle. What is less clear, however, is whether such labeling is always effective. To fill this gap, the current research paper aims to examine the positive and negative effects (double-edged effects) of a visual sweetness scale and identify the boundary condition.

Two studies were conducted using a 2 (cue type: scale vs text) by 2 (consumer type: novices vs experienced wine consumers) between-subjects, quasi-experimental design.

The double-edged effects are only significant among wine novices. Specifically, though wine novices are more likely to purchase wine with a sweetness scale (vs text) due to perceived diagnosticity (Study 1), they are unwilling to pay more due to low perceived quality (Study 2).

The study findings provide practical implications for wine producers, marketers and restaurants regarding when and how to use the sweetness scale on wine labels and wine service.

To the best of the authors’ knowledge, this research is the first to reveal the impact of visualizing wine style on wine labels. More importantly, while most previous research demonstrates the positive effects of using visual cues, this research sheds light on its drawbacks and examines the underlying mechanisms.

This paper aims to address the problem of double-diffusive magnetohydrodynamics (MHD) non-Darcy convective flow of heat and mass transfer over a stretching sheet embedded in a thermally-stratified porous medium. The controlling parameters such as chemical reaction parameter, permeability parameter, etc., are extensively discussed and illustrated in this paper.

With the help of appropriate similarity variables, the governing partial differential equations are converted into ordinary differential equations. The transformed equations are solved using the spectral homotopy analysis method (SHAM). SHAM is a numerical method, which uses Chebyshev pseudospectral and homotopy analysis method in solving science and engineering problems.

The effects of all controlling parameters are presented using graphical representations. The results revealed that the applied magnetic field in the transverse direction to the flow gives rise to a resistive force called Lorentz. This force tends to reduce the flow of an electrically conducting fluid in the problem of heat and mass transfer. As a result, the fluid velocity reduces in the boundary layer. Also, the suction increases the velocity, temperature, and concentration of the fluid, respectively. The present results can be used in complex problems dealing with double-diffusive MHD non-Darcy convective flow of heat and mass transfer.

The uniqueness of this paper is the examination of double-diffusive MHD non-Darcy convective flow of heat and mass transfer. It is considered over a stretching sheet embedded in a thermally-stratified porous medium. To the best of the knowledge, a problem of this type has not been considered in the past. A novel method called SHAM is used to solve this modelled problem. The novelty of this method is its accuracy and fastness in computation.

This study adds a new dimension in the study of racial and gender bias in farm lending. Most previous studies analyzed the separate effects of race and gender attributes on loan approval decisions. The analysis focuses on the stipulation of loan terms (loan amount, interest rate and maturity) among approved farm loan applications. The time period analyzed spans from 2004 until 2014 during which the government has undertaken reforms to improve delivery of loan services to its clientele of minority farmers. Thus, this study's findings could help validate the effectivity of such institutional reforms affecting Farm Service Agency (FSA) lending operations.

This study utilizes a national direct loan origination data from the FSA of the U.S. Department of Agriculture (USDA) collected from 2004 to 2014. The analysis begins by identifying significant differences in cross-tabulations of loan terms among different racial and gender classes. Seemingly unrelated regression (SUR) regression techniques are then applied for a system of equations involving the three loan packaging components. The combined effects of the prescribed loan packaging terms are subsequently analyzed under a simulation-optimization framework.

Regression results validate that indeed, relative to White American borrowers, certain minority borrowers are accommodated with lower loan amounts at higher interest rates and with shorter maturities. However, these decisions seem to be prompted by credit risk management considerations. The most compelling findings include the insignificance of all double minority labeling variables, except for the interest rate equation that even produced favorable results for Hispanic American females. Simulation-optimization results further reinforce that even when one or two unfavorable loan terms are included in the packaging, double minority borrowers end up with better profitability and liquidity positions.

This study provides a different perspective in dealing with the controversial minority bias in lending by presenting evidence gathered from a government farm lending institution. The USDA-FSA has been sued in numerous occasions by minority borrowers. Since then, however, it has deliberately implemented institutional reforms to rectify previous errors. This study provides empirical evidence strengthening FSA's claim of its intention to improve its delivery of loan services, especially for its socially disadvantaged borrowers with double minority classification.

This study pioneers the analysis of the double minority labeling effect on farm lending decisions. Its contributions to literature are further enhanced by its goal to validate the effectiveness of FSA institutional reforms undertaken since the early 2000s in order to improve credit access of and delivery of credit services to minority farm borrowers, especially those that belong to more than one minority classification.

The rapid development of the Internet has led to an increasingly significant role for E-commerce business. This study examines how the green supply chain (GSC) operates on the E-commerce online channel (resell mode and agency mode) and the traditional offline channel with information sharing under demand uncertainty.

This study builds a multistage game model that considers the manufacturer selling green products through different channels. On the traditional offline channel, the competing retailers decide whether to share demand signals. Regarding the resale mode of E-commerce online channel, just E-tailer 1 determines whether to share information and decides the retail price. In the agency mode, the manufacturer decides the retail price directly, and E-tailer 2 sets the platform rate.

This study reveals that information accuracy is conducive to information value and profits on both channels. Interestingly, the platform fee rate in agency mode will inhibit the effect of a positive demand signal. Information sharing will cause double marginal effects, and price competition behavior will mitigate such effects. Additionally, when the platform fee rate is low, the manufacturer will select the E-commerce online channel for operation, but the retailers' profit is the highest in the traditional channel.

This research explores the interplay between different channel structures and information sharing in a GSC, considering price competition and demand uncertainty. Besides, we also considered what behaviors and factors will amplify or transfer the effect of double marginalization.