This work compares a dealer market and a limit‐order book. Dealers commonly observe order flow and collect information from multiple market orders. They may be better informed than other traders, although they do not earn rents from this information. Dealers earn rents as suppliers of liquidity, and their decisions to enter or exit the market are independent of the degree of adverse selection. Introduction of a limit‐order book lowers the execution‐price risk faced by speculators and leads them to trade more aggressively on their information. Introduction of the book also lowers dealer profits, but increases the informational efficiency of prices.

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Journal of the Textile InstituteThe main purpose of this paper is to analyze the Turkish handmade carpet industry and to compare it with select Far East countries. In particular, the Turkish handmade carpet industry is compared with the handmade carpet industries of Iran, India, China, Afghanistan, Pakistan, and Nepal. In this context, the determinants of handmade carpets in the US market are analyzed empirically. Our results show that the Turkish handmade carpet industry has been experiencing a period of recession in the past decade. Through the relative comparative advantage (RCA) index and the Kreinin-Finger similarity (KFS) index, we observed that the RCA index for Turkey indicates that Turkey's RCA has been declining since 1992. However, despite this decline, the RCA of Turkey was above that of other countries until 1997. But after this, the advantage disappeared eventually and was gained by Iran. During this period, the other competitors of Turkey showed small increases. Furthermore, the empirical results from the gravity model suggests that a 10% real depreciation/appreciation of the US dollar against foreign currency leads to a 0.2% decrease/increase in imports. This finding suggests relatively low exchange rate import pass-through in carpet commodity. The results also support the Linder hypothesis that countries with similar preferences and demand structures will tend to trade more.

This study aims to identify quality improvement strategies for energy investments. For this purpose, a model is proposed which includes 4 different stages. In the first stage, the MCDM problem is identified for evaluating the service development for energy industry. In this framework, quality function deployment (QFD) approach is taken into consideration which includes both customer expectations and technical requirements at the same time to improve the quality in the organization. The second stage is related to the calculation of the correlation coefficients of decision matrices for the criteria by considering hesitant 2-tuple interval-valued Pythagorean fuzzy sets. The third stage includes the weighting of the customer expectations with hesitant 2-tuple interval-valued Pythagorean fuzzy (HIVPF) DEMATEL. In the final stage, TRIZ-based quality improvement strategies of energy investments are ranked by using 2-tuple HIVPF TOPSIS. Thus, the motivation of this study is to figure out the weights of the criteria for quality improvement strategies in energy investments. Also, the most important contribution of this study to the literature is related to the originality in the methodology by proposing a new MCDM model while using hesitant linguistic term sets, linguistic 2-tuple information, interval-valued Pythagorean fuzzy sets properly. The findings indicate that empathy is the most significant criterion for the customer expectations in the energy investments. In addition to this issue, it is also identified that customization is the best factor among the technical requirements of energy investments. Moreover, information and communication facilities and organizational background are found as the best competencies of new service development in energy investments. Furthermore, that prior action and periodic action are the most prominent strategies for quality improvement. While considering these results, it can be said that the pricing policy of the energy companies should be fair to increase customer satisfaction. Additionally, offering flexible payment opportunities on energy bills can have a positive influence on the customer satisfaction in this process. Also, preliminary planning of the project should be done in detail in energy investments. Owing to this issue, customers' preferences can be identified before the product is placed on the market. In addition, it can be possible to identify the risks that may arise in energy investments with the help of the periodical audits.

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The influences of five different fertilizer treatments on diversity of rhizobia in soybean nodule were investigated in a long-term experiment with with four replicates: (1) control (without fertilization), (2) balanced NPK fertilizer (NPK), and (3-5) unbalanced chemical fertilizers without one of the major elements (NP, PK, and NK) in Mollisol in Northeast China. The highest soybean yield was observed in the NPK treatment. Total of 200 isolates were isolated and grouped into four Bradyrhizobium genospecies corresponding to B. japonicum, B. diazoefficiens, B. ottawaense and Bradyrhizobium sp. I, based upon the multilocus sequence analysis of 6 housekeeping genes. The Bradyrhizobium sp. I was extensively distributed throughout the study site and was recorded as the dominant soybean rhizobia (82.5-87.5%). Except the NK treatment, the other fertilizer treatments had no effect on rhizobial species composition. Compared with the CK treatment, all the fertilizer treatments decreased species richness, diversity and evenness. The soil organic carbon contents, available N content and pH were the key soil factors to rhizobial community structure. Results suggest that long-term fertilization can decrease rhizobial species diversity, while balanced fertilization with NPK is the most suitable fertilization regime if taking both soybean yields and rhizobial diversity into account.

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Previous researches have considered that the impact of fashion change and fashion consumption is linear. Therefore, one reason was found as the ultimate source to explain why a fashion style/ trend was spread to the mass market. However, the existing market is complex and difficult to find out the holistic reason to explain fashion consumption. In this study, the chaotic perspective is taken into account to investigate the relationship between fashion change and fashion consumption. By using the grounded theory method, 33 in‐depth interviews were conducted. A chaotic fashion consumption model is developed from the findings to explain how different fashions are consumed and rejected while fashion changes. It is found that the interaction of being fashionable, perceived fashionability and system participation affects the ultimate decision on fashion consumption. It is also found that a pattern can be traced to forecast the degree of fashion consumption even when the fashion change phenomenon is chaotic. Thus, it is similar to the principle of chaos theory that short‐term prediction is possible in relation to the degree of fashion acceptance among consumers. Marketing implications are suggested with reference to the chaotic fashion consumption model.