ECONOMICS OF SOFTWARE DEVELOPMENT

In this paper, we investigate economics of software development. We first identify several dimensions of software quality from user’s perspectives. We model the tradeoff between having more features and functionalities and the ease of learning in usability, and the tradeoffs among ease of use, ease of learning, and usage frequency. Based on the impacts of quality dimensions on user’s utility, we analyze the software monopoly’s economic incentives to provide high quality software products and build analytical model to analyze the software company’s optimal design decisions. (Keywords: Software, Usability, Economics

Variety and volume dynamic management for value creation in changeable manufacturing systems

In today’s uncertain market and continuously evolving technology, managing manufacturing systems are more complex than ever. This paper studies the dynamics of managing variety and volume to enhance value creation in manufacturers implementing system-level advanced and automated manufacturing technology (AAMT). The demand is composed of heterogeneous customers who make purchasing decisions depending on the variety levels and lead times of the firm’s product offerings. The cost structure adopted calculates profit as the difference between customer value creation rate (VCR) and costs associated with the process of creating this value. Reported results contribute to the variety and volume management literature by offering analytical clarity of factors affecting product platforms and capacity scalability management for systems with AAMT. In addition, insightful answers to the trade-offs between profit maximising market coverage and investments, smoothing demand policies and system stability for this type of environment are presented. Furthermore, the value of market information in deciding the industrial technology investment and also the impact of product life cycle on the same investment is captured

The limits of planned obsolescence for conspicuous durable goods

An extensive body of literature argues for the benefits of planned obsolescence, the strategy of designing products with low durability to induce repeat purchases from the consumers and allow the firm to sell a larger volume. Yet, several firms avoid planned obsolescence and instead offer products with high durability. In this paper, we offer a demand-side rationale for a high-durability product design strategy: the exclusivity seeking consumer behavior associated with conspicuous consumption. In the presence of consumers who value exclusivity, we find that firms benefit from designing products with higher durability in conjunction with a high-price, low-volume introduction strategy. A higher durability in such a context leads to greater resale value, allowing the firm to charge a higher price and lower the sales volume to achieve the product exclusivity valued by the consumers. This contrasts with the planned obsolescence strategy that capitalizes on the high sales volume achieved by setting a low new product price. We also show that offering higher durability and charging a higher price are complementary levers to respond to consumers who value exclusivity. Our analysis unearths insights regarding the effect of exclusivity-seeking behavior on a firm’s demand and pricing. We show that firms’ durability choice may explain the joint increase in price and demand for conspicuous goods

Product Design with Attribute Dependence

[Abstract] This paper studies how product design and pricing strategies are affected by the existing relationship between the characteristics that integrate the product. The analysis shows that complementarity and low substitutability encourage the provision of quality incorporated to the products and increase the quality distortion and cannibalization problems that are common in segmented markets. A two-product strategy with a common attribute is shown to be a feasible strategy for reasons other than cost savings, namely attribute dependence. In addition, menu pricing is found to be the most profitable strategy, and a commonality strategy is more profitable than a common-product strateg

Pricing Software Upgrades: The Role of Product Improvement & User Costs

The computer software industry is an extreme example of rapid new product introduction. However, many consumers are sophisticated enough to anticipate the availability of upgrades in the future. This creates the possibility that consumers might either postpone purchase or buy early on and never upgrade. In response, many software producers offer special upgrade pricing to old customers in order to mitigate the effects of strategic consumer behavior. We analyze the optimality of upgrade pricing by characterizing the relationship between magnitude of product improvement and the equilibrium pricing structure, particularly in the context of user upgrade costs. This upgrade cost (such as the cost of upgrading complementary hardware or drivers) is incurred by the user when she buys the new version but is not captured by the upgrade price for the software. Our approach is to formulate a game theoretic model where consumers can look ahead and anticipate prices and product qualities while the firm can offer special upgrade pricing. We classify upgrades as minor, moderate or large based on the primitive parameters. We find that at sufficiently large user costs, upgrade pricing is an effective tool for minor and large upgrades but not moderate upgrades. Thus, upgrade pricing is suboptimal for the firm for a middle range of product improvement. User upgrade costs have both direct and indirect effects on the pricing decision. The indirect effect arises because the upgrade cost is a critical factor in determining whether all old consumers would upgrade to a new product or not and this further alters the product improvement threshold at which special upgrade pricing becomes optimal. Finally, we also analyze the impact of upgrade pricing on the total coverage of the market

The impact of product complexity on ramp-up performance

Fast product ramp-ups are crucial in consumer electronics because short product lifecycles prevail and profit margins diminish rapidly over time. Yet many companies fail to meet their volume, cost and quality targets and the ramp-up phase remains largely unexplored in new product and supply chain management research. This study identifies the key product characteristics that affect ramp-up performance using operational data from the cell phone industry. We investigate three research questions: (1) How to measure software and hardware complexity characteristics of consumer electronics products – and specifically cell phones? (2) To what extent drive product complexity characteristics manufacturing performance? and (3), in turn, to what extent drive manufacturing performance and complexity characteristics ramp up performance? The findings contribute to operations management literature in three ways: First, our model reflects the growing importance of software characteristics in driving hardware complexity, an aspect that prior empirical ramp-up studies have not yet addressed. Second, specific hardware and software complexity characteristics (i.e., component count, parts coupling and SW code size) primarily drive the performance of the manufacturing system in terms of final yield and effective capacity. And finally, effective capacity together with the novelty aspects of both software and hardware complexity (i.e., SW novelty and product novelty) are the key determinants of ramp-up performance

When should customers control service delivery? Implications for service design

What do a Mongolian stir-fry restaurant and a medical lab providing home testing solutions have in common? They are both innovative services that base their success on customers controlling part of the service delivery. These providers allow service tasks to be performed by the customers as a means of shaping the overall experience and not strictly as a means of "outsourcing" the service. Motivated by such practices, we explore whether and how should providers allocate the control of different tasks of their service to the customers. We model services as multi-step processes with each step affecting customers' experience at other steps. At certain steps the provider may hold an “expert" role and be more capable of performing than the customers, whereas at other steps she holds an “administrative" role and is less capable of performing than the customers. We distinguish between routine services, where the service outcome must conform to standardized specifications, and non-routine services, where the value of the service outcome relies on subjective dimensions. We show that the optimal design is determined by an economically intuitive rule whereby the provider controls the steps based on the marginal benefit she can derive compared to self-service. For routine services, this rule translates to managing “blocks" of steps because the provider benefits from containing the volatility of the experiences across the service even when this implies the provision of service steps with a negative marginal benefit, i.e., steps which she is less capable of performing than the customers. Instead, in non-routine services providers should focus on the value advantage they can ensure through a "core provision" even if this implies forgoing control of steps for which they are more capable of performing than the customers and from which they can derive positive marginal benefit. This implies that in non-routine services the provider exercises more control up to a certain process length; beyond that she delegates more steps to the customers. When customers differ in their abilities to perform the different steps, the provider may offer a service line. Service lines facilitate better segmentation than a single service offering, but their economic benefit exhibits an inverted “U-shaped" relationship with respect to the number of steps that a service comprises. Finally, we find that competition between two providers who differ in their capabilities to perform a service results in service design differentiation where the more capable provider offers a higher-end "focused service" against a lower-end "super-service" offered from the less capable provider

How does development lead time affect performance over the ramp-up lifecycle? : evidence from the consumer electronics industry

In the fast-paced world of consumer electronics, short development lead times and efficient product ramp-ups are invaluable. The sooner and faster a firm can ramp-up production of a new product, the faster it can start to earn revenues, profit from early market opportunities, establish technology standards and release scarce development resources to support new product development projects. Yet, many companies fail to meet their time-to-market and time-to-volume targets and the complex interrelationships between product characteristics, development lead time and ramp-up performance are largely unexplored. In response to these limitations our study focuses on three research questions: (1) To what extent is ramp-up performance determined by development lead time and product complexity? (2) How do these relationships change in the course of the ramp-up lifecycle? and (3) How can the results be explained? Our results contribute to the field of operations management in three ways. First, we offer a more comprehensive and enriched analysis of the drivers for development lead time and ramp-up performance in the cell phone industry. Second, we demonstrate that late schedule slips – although disastrous for customer relations in which due dates are crucial – provide the opportunity to build up (semi-finished) product buffers which in turn increase the initial ramp-up performance. Third, we show that it is important to take these effects into account in a jointly and lifecycle-dependent manner. Thus, our insights support management efforts to anticipate the consequences of product design decisions, predict development schedule risk levels, and make informed decisions about production volume commitments

The Optimal Pace of Product Updates

Some firms (such as Intel and Medtronics) use a time–pacing strategy for new product development, introducing new generations at regular intervals. If the firm adopts a fast pace (introducing frequently) then it prematurely cannibalizes its old generation and incurs high development costs, while if it waits too long, it fails to capitalize on customer willingness–to–pay for more advanced technology. We develop a model to gain insight into which factors drive the pace. We consider the degree to which a new generation stimulates market growth, the rate at which it diffuses (its coefficients of innovation and imitation), the rate of decline in its margin over time, and the cost of new product development. The optimization problem is non–concave; however we are able to solve it numerically for a wide range of parameters because there is a finite number of possible solutions for each case. Somewhat intuitively, we find that a faster pace is associated with a higher market growth rate and faster margin decay. Not so intuitively, we find that relatively minor differences in the new product development cost function can significantly impact the optimal pace. Regarding the Bass coefficients of innovation and imitation, we find that a higher sum of these coefficients leads to a faster pace but with diminishing effects, and that for relatively higher sums the coefficients are effectively substitutes

An interactive product development model in remanufacturing environment: a chaos-based artificial bee colony approach

This research presents an interactive product development model in re-manufacturing environment. The product development model defined a quantitative value model considering product design and development tasks and their value attributes responsible to describe functions of the product. At the last stage of the product development process, re-manufacturing feasibility of used components is incorporated. The consummate feature of this consideration lies in considering variability in cost, weight, and size of the constituted components depending on its types and physical states. Further, this research focuses on reverse logistics paradigm to drive environmental management and economic concerns of the manufacturing industry after the product launching and selling in the market. Moreover, the model is extended by integrating it with RFID technology. This RFID embedded model is aimed at analyzing the economical impact on the account of having advantage of a real time system with reduced inventory shrinkage, reduced processing time, reduced labor cost, process accuracy, and other directly measurable benefits. Consideration the computational complexity involved in product development process reverse logistics, this research proposes; Self-Guided Algorithms & Control (S-CAG) approach for the product development model, and Chaos-based Interactive Artificial Bee Colony (CI-ABC) approach for re-manufacturing model. Illustrative Examples has been presented to test the efficacy of the models. Numerical results from using the S-CAG and CI-ABC for optimal performance are presented and analyzed. The results clearly reveal the efficacy of proposed algorithms when applied to the underlying problems. --Abstract, page iv