Informs 2015

446 / 552

INFORMS Philadelphia – 2015
444
WC54
54-Room 108A, CC
Service Science I
Contributed Session
Chair: Oleg Pavlov, Associate Professor Of Economics And System
Dynamics, WPI, SSPS, 100 Institute Rd., Worcester, MA, 01609,
United States of America,
1 - Demand Management and Optimal Workforce Scheduling in
Professional Service Firms
Vincent Hargaden, University College Dublin, Engineering &
Materials Science Centre, Belfield, Dublin 4, Ireland,
Jennifer Ryan, Amir Azaron
We analyse the workforce planning process in professional services firms from a
demand management perspective. Taking a project network approach, we
develop a multi-objective optimization model, which minimizes both the total
direct costs of project staff and the maximum delay from the scheduled durations
across all projects. The result is a better utilization of the firm’s workforce, while
maintaining customer satisfaction.
2 - Strategies for Planning the ICT Convergence-based PSS Value
Chain in Manufacturing Companies
Hosun Rhim, Professor Of Logistics, Service, And Operations
Management, Korea University Business School, Anam-dong,
Seongbuk-gu, 136-701, Seoul, Korea, Republic of,
, Yong Yoon
The ICT convergence-based Product Service Systems (PSS) is a migration strategy
to be adopted for the manufacturers in the PSS business model planning stage.
The structured process and the critical factors in that stage will be investigated.
The analytic hierarchy process (AHP) has been implemented to organize and
analyze a series of decisions.
3 - Exploiting Learning in Call Center Routing Decisions
Tom Robbins, Associate Professor, East Carolina University,
College of Business, 3212 Bate Building, Greenville, NC, 27858,
United States of America,
We explore a call center environment where agents increase their productivity
over time, but eventually quit. We consider a routing policy that attempts to
exploit this situation and improve long-term call center performance. We
examine policies where calls are routed to the most experienced agents when the
call center is busy, to facilitate efficiency, and to the least experienced agent when
the call center is slow, to facilitate learning.
4 - Education as a Service System
Oleg Pavlov, Associate Professor Of Economics And System
Dynamics, WPI, SSPS, 100 Institute Rd., Worcester, MA, 01609,
United States of America, , Frank Hoy
Service science is an emerging discipline rooted in system science. Applied to
education, the service science methodology views universities and academic
programs as service systems that go through life-cycles. We study
entrepreneurship education programs that are gaining in popularity, yet are
notoriously difficult to build up and sustain. We describe them as educational
service systems, review different program deployment models and identify factors
that lead to their success or failure.
WC55
55-Room 108B, CC
Decision Analysis II
Contributed Session
Chair: Yudhi Ahuja, Associate Professor, San Jose State University, One
Washington Square, San Jose, CA, 95192, United States of America,
1 - Social Norms and Identity Dependent Preferences
Daphne Chang, School of Information, University of Michigan,
105 S. State Street, 3336 North Quad, Ann Arbor, United States
of America, Erin Krupka, Roy Chen
In our paper, we test the impact of norms on social identity driven choice by
using a 2 (identity prime) x 2 (frame) x 2 (choice or norms) experimental design
to separately and directly elicit empirical measures of identity dependent norms
for eleven different redistribution situations. We demonstrate that including
identity dependent norms improves our ability to predict behavior. Further, we
estimate a key structural parameter of the social identity modelóidentity
dependent norm sensitivity.
2 - Combining Forecast Quantiles – A Numerical Investigation
Chen (mavis) Wang, Assistant Professor, Tsinghua University,
Shunde Bldg. S609, Beijing, 100084, China,
, Shu Huang, Vicki Bier
We review statistical methods for combining forecast quantiles from multiple
experts, including equal weighting aggregation (by finding the average quantile,
average probability, median quantile, or median probability), and performance-
based weighting aggregation. We also propose a Bayesian quantile regression
model to estimate location and precision biases and a more flexible Bayesian
nonparametric model. We compare them using both simulation and a large
dataset on expert opinion by Cooke.
3 - Approximate Representation for Time Series and its Application
to Efficient State Estimation
Jianjun Lu, Associate Professor, China Agricultural University,
No. 17, Qinghuadong Road, Haidian Distri, Beijing, 100083,
China,
We propose an approximate representation of multivariate time series by using
the representative time series called latent time series based on covariance
structure analysis where correlation among observed time series is utilized. The
dynamic factor analysis for multivariate time series is extended. To avoid the
whole estimation of state variable to each nonlinear system, we apply Particle
Filters only for latent time series, and for another observed time series we use
these estimated states.
4 - Forecasting Trends of Immigration to United States of America
Yudhi Ahuja, Associate Professor, San Jose State University,
One Washington Square, San Jose, CA, 95192,
United States of America,
This paper deals with immigration statistics to United States of America from all
over the globe. The future trends of immigrants have been estimated and their
distributions over various States worked out. The paper concludes with
implications of immigration on the economy, employment, education and social
benefits.
5 - Integrated Fuzzy Approach for Analyzing Risk Analysis in Product
Recovery System
Dr Jitender Madaan, Professor, Dept Of Management Studies,
Indian instititute of Technology Delhi, Hauz Khas, New Delhi,
110016, India, , Divya Chaoudhry
Paper proposes proposes a novel methodology based on fuzzy set theory and
evidential reasoning algorithm for quantifying the risks to capture the
uncertainties of recovery system operations. It has practical implications for the
organizations involved in product recovery to guide strategy formulation for the
pro-active mitigation of risks. Moreover, paper would provide insights to the
managers for enhancing the robustness of recovery systems along with better
management of disruptions.
WC56
56-Room 109A, CC
Manufacturing I
Contributed Session
Chair: Felix Papier, Associate Professor, ESSEC Business School,
Avenue Bernard Hirsch, Cergy, 95021, France,
1 - Managing Product Variety through Developing Vanilla Boxes using
Hierarchical Clustering
Pooya Daie, Concordia University, 1455 De Maisonneuve Blvd.
W., Montreal, QC, H3G 1M8, Canada, ,
Simon Li
This paper focuses on implementing mass customization through development of
semi-finished vanilla boxes to reduce supply chain cost.The challenge is that the
possible number of vanilla boxes grows dramatically with increase in number of
product solution,the basic information of product variety is captured
in a matrix format,specifying the component requirements for each product
variant.Then,hierarchical clustering is applied over the components with the
considerations of demands
2 - Tailor Made: Make-to-order Decisions at the Bottom of the
Apparel Supply Chain
Suri Gurumurthi, Visiting Asst. Professor, HKUST, Clearwater
Bay, Kowloon, HK, Hong Kong - PRC,
I discuss make-to-order strategies considered by apparel component suppliers at
the bottom of the supply chain. The prevalent models for make-to-order decisions
focus on decision-makers at the upper tiers of supply chains. I discuss make-to-
order decisions at lower tier decision-makers who are subject to extremes of
demand variability, but that also compete with very slim margins.
WC54