In a recent blogpost,
I wrote about time-based competition, and how supply chain network firms could gain a competitive advantage through quantifying the time associated with their supply chain network activities from production through delivery to their customers and
how they could compete with time.
Quality is another dimension that is essential to excellence whether in the product or the services domain.
Just last weekend, my husband and I drove through the countryside to one of our favorite breakfast places, located in Ashfield, Massachusetts, close to a beautiful lake, where we purchase the best baguettes outside of Paris. We had been there several times before but this time when it took almost an hour to get our eggs and toast, it was clear that something had happened to the quality of service.
I watched the waitress, who, rather than bringing a full order to a table, walked back and forth to just deliver a single cup of coffee at a time. Was this a work slowdown that we were experiencing or some interesting work dynamics? As someone who works on optimizing business and other processes and really cares about efficiency, this was painful to watch and our stomaches were growling. I, finally, went up to the waiter, who was responsible for the customers in the other room, and put in our order.
The displeasure was notable and once the order finally arrived the manager came by and said that we would not be charged for our breakfast. Indeed, the quality of the experience was so low, that the only fair price was ZERO! Of course, we tipped the waiter and the manager saw this.
We have been doing a lot of research on supply chain network competition and that was the major theme in the Supply Chain Network Economics book that I wrote while I was
a Radcliffe Institute for Advanced Study Fellow at Harvard University on my previous sabbatical.
How firms compete not only on the differentiated products that they produce but also on the quality of their products and how the underlying network economics of the competition evolves and leads to prices, quality levels, and product flows, is a topic that has fascinated me and my students lately.
Indeed, quality is emerging as an important feature/characteristic in numerous products, ranging from food to pharmaceuticals to durable manufactured products such as automobiles to high tech products, including microprocessors and even services associated with the Internet. It has been argued that firms, in reality, do not differentiate their products to make them different, or to give consumers more variety but, rather, to make them better so that consumers purchase the firm’s product. Moreover, although the differentiated product may even cost more to produce, it may result in higher profits since consumers may be drawn to such products. Hence, quality is implicit in product differentiation.
In a recent paper,
"A Dynamic Network Oligopoly Model with Transportation Costs, Product Differentiation, and Quality Competition," Anna Nagurney and Dong Li, which we will be presenting at the upcoming INFORMS conference in Phoenix, Arizona, and at the North American Regional Science Association Conference on Ottawa, Canada, we developed a supply chain network oligopoly model with differentiated products and quality levels. The framework is that of Cournot-Nash competition in which the firms compete by determining their optimal product shipments as well as the quality levels of their particular products. In addition to the model development, we obtained stability analysis results, and also proposed a discrete-time algorithm for the dynamic tracking of the continuous-time trajectories of the firms’ product shipments and quality levels over time.
The static and dynamic network models that we constructed in this paper generalize former models in several
significant ways, while retaining the spatial component in that:
(1). We consider product differentiation;
(2). We incorporate quality levels associated with the individual firms’ products, as strategic variables, along with the product shipments, and we include the associated total costs as well as appropriate demand price functions at the demand markets, and
(3). We capture the critical transportation costs associated with linking the production side with the demand markets via a network.
In addition, we provided both qualitative analysis as well as an algorithmic scheme, along with numerical examples, which is made possible through projected dynamical systems theory, which can handle constraints and the associated discontinuities, unlike classical dynamical systems theory. Projected dynamical systems was the topic of the book that I wrote with Dr. Ding Zhang. It was
the second volume in the
International Series in Operations Research & Management Science.
.JPG)
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