The Effects of Market Orientation on New Product Performance and Innovation Speed (A Case Study: Malayer Furniture Workshops)

Ever increasing change in the lifestyles and with the emergence of the middle class in Iran, the furniture industry has become one of the most demanded and most competitive industries in Iran. In this industry, the knowledge of market orientation, the speed of innovation and the performance of new products, plays a major role in the competitiveness of furniture manufacturing workshops. The purpose of the present research is to investigate the effect/s of market orientation on new product performance and innovation speed. In terms of purpose and research type, it is a descriptive-co relational one. The statistical population of the study was 280 managers and owners of furniture manufacturing workshops in the city of Malayer. Using Morgan table, 162 subjects were selected through a targeted sampling method. Data gathering tools were Litis et.al (2014), Innovation Speeding Questionnaire by Shaun et al. (2016) and Lynn et al. (2000) with a five-point Likert scale. The reliability of the questionnaires was confirmed by Cronbach's alpha method and for data analysis, structural equation modeling and PLS software were used. The findings of this study confirmed that market orientation had a positive and significant effect on the performance of new product and the speed of innovation. Keywords: market orientation, innovation speed, new product performanc

Exploring Differential Obliviousness

In a recent paper, Chan et al. [SODA \u2719] proposed a relaxation of the notion of (full) memory obliviousness, which was introduced by Goldreich and Ostrovsky [J. ACM \u2796] and extensively researched by cryptographers. The new notion, differential obliviousness, requires that any two neighboring inputs exhibit similar memory access patterns, where the similarity requirement is that of differential privacy. Chan et al. demonstrated that differential obliviousness allows achieving improved efficiency for several algorithmic tasks, including sorting, merging of sorted lists, and range query data structures. In this work, we continue the exploration of differential obliviousness, focusing on algorithms that do not necessarily examine all their input. This choice is motivated by the fact that the existence of logarithmic overhead ORAM protocols implies that differential obliviousness can yield at most a logarithmic improvement in efficiency for computations that need to examine all their input. In particular, we explore property testing, where we show that differential obliviousness yields an almost linear improvement in overhead in the dense graph model, and at most quadratic improvement in the bounded degree model. We also explore tasks where a non-oblivious algorithm would need to explore different portions of the input, where the latter would depend on the input itself, and where we show that such a behavior can be maintained under differential obliviousness, but not under full obliviousness. Our examples suggest that there would be benefits in further exploring which class of computational tasks are amenable to differential obliviousness

Exploring Differential Obliviousness

In a recent paper Chan et al. [SODA '19] proposed a relaxation of the notion of (full) memory obliviousness, which was introduced by Goldreich and Ostrovsky [J. ACM '96] and extensively researched by cryptographers. The new notion, differential obliviousness, requires that any two neighboring inputs exhibit similar memory access patterns, where the similarity requirement is that of differential privacy. Chan et al. demonstrated that differential obliviousness allows achieving improved efficiency for several algorithmic tasks, including sorting, merging of sorted lists, and range query data structures. In this work, we continue the exploration and mapping of differential obliviousness, focusing on algorithms that do not necessarily examine all their input. This choice is motivated by the fact that the existence of logarithmic overhead ORAM protocols implies that differential obliviousness can yield at most a logarithmic improvement in efficiency for computations that need to examine all their input. In particular, we explore property testing, where we show that differential obliviousness yields an almost linear improvement in overhead in the dense graph model, and at most quadratic improvement in the bounded degree model. We also explore tasks where a non-oblivious algorithm would need to explore different portions of the input, where the latter would depend on the input itself, and where we show that such a behavior can be maintained under differential obliviousness, but not under full obliviousness. Our examples suggest that there would be benefits in further exploring which class of computational tasks are amenable to differential obliviousness

Impact of Long-term Debt on Overinvestment Problem of Agency

Business units are always faced with investment opportunities and need to make logical decisions on an optimal investment. Indeed, the investment of each business unit should be done with regard to the resource constraints and its effectiveness through the criteria for evaluating the projects including the net present value (NPV). The paper aims to investigate the effect of long-term debt on the overinvestment of agency problem. The present research is applied in terms of its purpose and it is descriptive and correlation in terms of nature. The statistical population of the study was the financial information related to the performance of 540 companies listed in Tehran Stock Exchange during 2011 and 2015. 152 companies were selected by the systematic elimination sampling. The data collection was carried out using the Tadbir Pardaz and Rahavard-e-Novin software as well as the Research Management, Islamic Studies and Development of Stock Exchange Organization and Stock Exchange Organization websites. The research data are hybrid. The data were analyzed using the F-Limer and Hausman tests using Eviews9 software. Based on the results, the pre-investment declined by 36% at a significant level less than 0.05% while increasing long-term debt by 1%, and the overinvestment reduces 69% by a one-percent increase in the financial leverage

On Selective-Opening Security of Deterministic Primitives

Classically, selective-opening attack (SOA) has been studied for randomized primitives, like randomized encryption schemes and commitments. The study of SOA for deterministic primitives, which presents some unique challenges, was initiated by Bellare et al. (PKC 2015), who showed negative results. Subsequently, Hoang et al. (ASIACRYPT 2016) showed positive results in the non-programmable random oracle model. Here we show the first positive results for SOA security of deterministic primitives in the standard (RO devoid) model. Our results are: \begin{itemize} \item Any $2t$-wise independent hash function is SOA secure for an unbounded number of ``$t$-correlated\u27\u27 messages, meaning any group of up to $t$ messages are arbitrarily correlated. \item An analogous result for deterministic encryption, from close variant of a NPROM scheme proposed by Hoang et al. \item We connect the one-more-RSA problem of Bellare et al. (J.~Cryptology 2003) to this context and demonstrate this problem is hard under the $\Phi$-Hiding Assumption with large enough encryption exponent. \end{itemize} Our results indicate that SOA for deterministic primitives in the standard model is more tractable than prior work would indicate

A Framework for Stabilizing the Person-Organization Relationship

In many organizational interactions,the employee and the organization have different understandings of the obligations of each party and how to fulfill their obligations.Divergence of these perceptions can lead to misunderstandings,conflicts and even breaches of contract.The main purpose of this study is to "provide a framework for stabilizing the employee-organization relationship,studied:Snapp".This research is applied-developmental in terms of purpose and mixed method in terms of approach and descriptive-survey in terms of data collection method.The statistical population used in this study were Snapp managers and experts in middle and senior levels and the sample size was 15 Snapp organizational experts.To select these people,targeted sampling and snowball sampling methods were used.In this study,interpretive structural modeling(ISM) and MICMAC analysis were used to identify the criteria and explore the relationships between them,After studying the literature and conducting in-depth semi-structured interviews with the sample size.Findings of the study showed the extraction of six components "employee characteristics,cultural characteristics,structural factors, governance model, policy rationality and environmental context" in a four-level ISM graph. Environmental contexts and policy rationality were identified as the most effective components and employee characteristics as the most impressive component in stabilizing the relationship between the employee and the organization

Instantiability of Classical Random-Oracle-Model Encryption Transforms

Extending work leveraging program obfuscation to instantiate random-oracle-based transforms (e.g., Hohenberger et al., EUROCRYPT 2014, Kalai et al., CRYPTO 2017), we show that, using obfuscation and other assumptions, there exist standard-model hash functions that suffice to instantiate the classical RO-model encryption transforms OAEP (Bellare and Rogaway, EUROCRYPT 1994) and Fujisaki-Okamoto (CRYPTO 1999, J. Cryptology 2013) for specific public-key encryption (PKE) schemes to achieve IND-CCA security. Our result for Fujisaki-Okamoto employs a simple modification to the scheme. Our instantiations do not require much stronger assumptions on the base schemes compared to their corresponding RO-model proofs. For example, to instantiate low-exponent RSA-OAEP, the assumption we need on RSA is sub-exponential partial one-wayness, matching the assumption (partial one-wayness) on RSA needed by Fujisaki et al. (J. Cryptology 2004) in the RO model up to sub-exponentiality. For the part of Fujisaki-Okamoto that upgrades public-key encryption satisfying indistinguishability against plaintext checking attack to IND-CCA, we again do not require much stronger assumptions up to sub-exponentiality. We obtain our hash functions in a unified way, extending a technique of Brzuska and Mittelbach (ASIACRYPT 2014). We incorporate into their technique: (1) extremely lossy functions (ELFs), a notion by Zhandry (CRYPTO 2016), and (2) multi-bit auxiliary-input point function obfuscation (MB-AIPO). While MB-AIPO is impossible in general (Brzuska and Mittelbach, ASIACRYPT 2014), we give plausible constructions for the special cases we need, which may be of independent interest

Multi-project Optimal Scheduling Considering Reliability and Quality Within the Construction Supply Chain: A Hybrid Genetic Algorithm

Although the construction industry, especially because of its relationship with other economic sectors, is one of the most important sectors that plays a key role in a country's economic growth, the construction supply chain has been considered less attention. Therefore, construction supply chain network design is of great importance for not only the companies but also governments. Thus, presenting an original mixed integer linear programming model, this paper introduces an optimal framework for a multi-project multi-resource multi-supplier construction supply chain network design for large construction companies with a decentralized procurement strategy. The main objective is to design a reliable supply chain model based on the quality of projects under the certain predefined budget, considering the entire supply chain as a single entity. Using a bi-objective approach to formulate the chain and the Lp-metric approach to solve the problem, make it possible to obtain a single-objective structural framework to reliability-quality trade-off consideration. To solve the problem in small and medium scales, GAMS software is employed, and a hybrid algorithm based on Genetic Algorithm (GA) and Simulated Annealing (SA) algorithm is developed to solve the large-scaled problem. The results show the capability of the model to attain optimal size of the chain as well as the quality-reliability trade-off considering a pre-specified budget. And, to the best of authors knowledge this is the first to obtain such a structured integrated framework in the construction supply chain

Coordinating of overcurrent relay in distribution system using linear programming technique

Power system includes many variety of equipment. A lot more amount of circuit breakers and relays are necessary to protect the system. The relays in the power system should be coordinated correctly so as to prevent mal-operation and therefore to avoid the unneeded outage of healthy section of the system. The overcurrent relays are usually the foremost protection product in a distribution system. Overcurrent relay is typically used as backup protection. But in a number of situations it may become the only protection supplied. A relay should get sufficient possibility to protect the area under its main protection. Just if the main protection does not clean the fault, the actual back-up Protection must start tripping, and as a result, overcurrent relay coordination in power distribution system is a important issue of protection engineer. The overcurrent relay coordination in ring fed distribution systems is a very constrained optimization trouble. The purpose is usually to discover an optimum relay setting to minimize the time of interruption of the power source and to stay away from the mal-operation of relay. This research talks about linear programming technique for optimum coordination of overcurrent relays in a ring fed distribution system