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This article has been withdrawn as it was published elsewhere and accidentally duplicated. The original article can be seen here: 10.1108/EUM0000000001513. When citing the article, please cite: Yeong Wee Yong, Kau Ah Keng, Tan Leng Leng, (1989) “A Delphi Forecast for the Singapore Tourism Industry: Future Scenario and Marketing Implications”, International Marketing Review, Vol. 6 Iss: 3.

This article has been withdrawn as it was published elsewhere and accidentally duplicated. The original article can be seen here: 10.1108/EUM0000000001513. When citing the article, please cite: Yeong Wee Yong, Kau Ah Keng, Tan Leng Leng, (1989) “A Delphi Forecast for the Singapore Tourism Industry: Future Scenario and Marketing Implications”, International Marketing Review, Vol. 6 Iss: 3.

This study aims to investigate the influence of brand familiarity, consumer green consciousness (GC) and chronic regulatory focus on consumer attitudes, buying intentions and willingness to pay more for eco-friendly products in a comparison between eco-friendly and non-eco-friendly products among Generation Z consumers.

An experiment with a between-subjects design was conducted with 151 Malaysian Generation Z consumers.

When consumers are more familiar with an eco-friendly brand than a non-eco-friendly brand, their attitude toward, buying intention and willingness to pay more for eco-friendly products are significantly higher than for non-eco-friendly products. In contrast, such effects are not significant when consumers are more familiar with a non-eco-friendly brand than an eco-friendly brand. Hence, young consumers are more inclined to favor a familiar eco-friendly brand than a familiar non-eco-friendly one. Consumers with higher GC are willing to pay more than consumers with lower GC for products of a familiar eco-friendly brand. When consumers are less familiar with an eco-friendly brand, those with a higher chronic promotion focus (CPF) will have a more favorable attitude toward, and a higher intention to buy, eco-friendly products than those with a lower CPF.

Awareness of how these factors influence consumer purchase behavior can help retailers and marketers design and communicate specific messages to highlight their brand and product eco-friendliness in their marketing strategies. Doing so may increase familiarity with their brand and the demand for and purchase of their brand’s eco-friendly products.

This research explores the influence of an integrated model of brand familiarity, GC and CPF on consumer purchase behavior in the comparison between eco-friendly and non-eco-friendly products. This has not been clearly examined in previous research.

This paper investigates the effects of information asymmetry and Credit Rating Agency's reputation on bond yield spread, which is caused by the split bond rating of CRAs. For analysis, We do multivariate analysis, using bond rating and bond yield spread data in Korea from 2004 to 2015. The empirical results are as follows.

First, we examines whether information asymmetry affects the bond yield spread. using split rating data. As a result, the information asymmetry measured by split rating variable is significant, which supports the information asymmetry hypothesis. Additionally we can find bond yield spread is decided by negative credit grade rather than positive credit grade under split rating condition.

Next, we examines the relationship between the CRA’s reputation and the bond yield spread in case of split rating. Here, samples were divided into full samples and split rating samples. Summarizing the result, both samples are suggest similar result, the bond yield spread is changed depending on the specific CRA’s grading which having conservative rating tendency.

Thus, This result suggest information asymmetry caused by split rating and CRA’s reputation measured by CRA’s rating tendency affect bond yield spread in Korea

This study examines the effect of a regulatory-focused prime (i.e. a brochure with a picture and message) on the recommending behavior of investment advisers in the context of an investment decision.

Three experiments were conducted with 468 participants, mostly from the financial services industry. Study 1 examined the direct effect of a regulatory-focused prime on an investment adviser's recommending behavior, whereas Study 2 examined the moderating role of regulatory fit on such behavior. Study 3 validated the findings.

The results provide evidence that a message using visual and textual cues based on a promotion and prevention regulatory focus may trigger a preference in an investment adviser's product recommendation. A promotion (prevention)-focused framed message will trigger the recommendation of an investment plan with a higher but riskier (safe and stable) potential return. However, when the same prime is presented with details of a performance incentive scheme, the effect of the prime is reduced when there is a regulatory nonfit between the prime and the message relating to the performance incentive scheme.

The findings highlight the importance of understanding how regulatory-focused stimuli may subconsciously influence the recommendation of investment advisers as heuristics used in decision-making, thereby influencing their clients' investment decisions.

Past studies have focused on how regulatory-focused visual and message cues influence consumer decision-making. This study provides empirical evidence regarding the influence of regulatory-focused prime on an investment adviser's behavior when providing investment advice.

The purpose of this paper is to apply the multidimensional construct of green perceived value (GPV) to the buying behavior of green food products to enhance the understanding of consumer behavior intentions and explain the formation of the intention to buy green food products.

This study adopted four GPVs (i.e. functional value, conditional value, social value and emotional value) and explored the relationships among GPV, attitudes and purchase intention. A total of 300 self-administered questionnaires were distributed, from which 253 usable responses were obtained.

The relationships between six constructs and 20 indicators were measured using structural equation modeling. All the underlying dimensions had a significant effect on consumers’ attitudes, significantly affecting their purchase intention.

Implications for future research and marketing strategies in the field of purchasing behaviors of green food products are discussed.

As a transition economy, China is interested in allocating its limited innovation resources economically, reasonably and efficiently to produce as many outputs as possible with its limited financial and human resources. Nonetheless, what is the efficiency of the allocation of innovative resources for civil–military integration enterprises, and what factors hinder its efficiency improvement? The purpose of this paper is to explore these problems.

The improved two-stage network data envelopment analysis (DEA) method is used to measure the overall efficiency and stage efficiency of the innovation resource allocation of 58 Chinese civil–military integration listed companies from 2010 to 2016. Tobit model is used to analyze the influencing factors of resource allocation efficiency.

The results indicate that the overall efficiency and stage efficiency of innovation resource allocation fluctuate in varying degrees during the period. The optimization of overall efficiency is restricted by lower efficiency of innovation achievement transformation. Enterprise scale was found to have a significant negative impact on both overall and two-stage efficiencies. Proportion of research and development (R&D) personnel had a positive effect on the overall and two-stage efficiency. Government support had a significant positive effect on the stage of innovation resource development and overall efficiency.

Previous research studies have used either the DEA or stochastic frontier analysis method to measure the efficiency of innovation activities as a whole and ignored the stage of initial investment to final output in innovation activities. That is, the process in which initial input of R&D resources becomes innovation output, and then becomes economic benefits. Therefore, this paper studies the efficiency of innovation resource allocation of civil–military integration listed companies. The improved two-stage chain network DEA method and Tobit model were used.

This paper proposes two alternative methods which are used for pricing the theoretical value of the KTB futures on the non-traded underlying asset; first method is to use the CKLS model, under which the volatility of interest rate changes is highly sensitive to the level of the interest rate, and then employ binomial trees to compute the theoretical value of futures, second one is to use the multifactor Vasicek model considering correlations between yields-to-maturity and then employ the Monte Carlo simulation to compute it. In the empirical study on KTB303 and KTB306, an CKLS methodology is superior to the conventional KORFX method based on the cost-of-carry model in terms of the size of difference between market price and theoretical price. However, the phenomena, the price discrepancy using the KOFEX methodology is very small for all test perlod, implies that the KOFEX one is being used for the most market participants. The reasons that an multifactor Vasicek methodlogy is performed poorly in comparison to another methods are 1) the Vasicek model might be not a good model for explaining the level of interest rates, or 2) the important point considered by the most market participants may be on the volatility or interest rate, not on the correlations between yields-to-maturity.

Efficient market hypothesis implies that the past price movements do not help forecast future price movements. Thus, it is impossible to consistently benefit by a technical trading strategy. On the other hand, technical analysts claim that the historical price movements are useful in predicting future price movements. These two lines of arguments are mutually contradictory. This paper reasonably assumes that the more efficient markets are, the worse will be the investment performance of technical analysis, and that as financial market‘s trading volume grows and with the elapse of time, the efficiency of markets should improve. This implies that after the launch of a new financial asset, market efficiency would improve with increased trading and elapsed time. In this paper, the duration analysis technique is used as a forecasting model and applied to measure the efficiency of Korean futures market and the won/dollar exchange rate market.

The design process of a bio-model involves multiple factors including data acquisition technique, material requirement, resolution of the printing technique, cost-effectiveness of the printing process and end-use requirements. This paper aims to compare and highlight the effects of these design factors on the printing outcome of bio-models.

Different data sources including engineering drawing, computed tomography (CT), and optical coherence tomography (OCT) were converted to a printable data format. Three different bio-models, namely, an ophthalmic model, a retina model and a distal tibia model, were printed using two different techniques, namely, PolyJet and fused deposition modelling. The process flow and 3D printed models were analysed.

The data acquisition and 3D printing process affect the overall printing resolution. The design process flows using different data sources were established and the bio-models were printed successfully.

Data acquisition techniques contained inherent noise data and resulted in inaccuracies during data conversion.

This work showed that the data acquisition and conversion technique had a significant effect on the quality of the bio-model blueprint and subsequently the printing outcome. In addition, important design factors of bio-models were highlighted such as material requirement and the cost-effectiveness of the printing technique. This paper provides a systematic discussion for future development of an engineering design process in three-dimensional (3D) printed bio-models.